File size: 248,906 Bytes
6493548
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
1548
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
1635
1636
1637
1638
1639
1640
1641
1642
1643
1644
1645
1646
1647
1648
1649
1650
1651
1652
1653
1654
1655
1656
1657
1658
1659
1660
1661
1662
1663
1664
1665
1666
1667
1668
1669
1670
1671
1672
1673
1674
1675
1676
1677
1678
1679
1680
1681
1682
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
1693
1694
1695
1696
1697
1698
1699
1700
1701
1702
1703
1704
1705
1706
1707
1708
1709
1710
1711
1712
1713
1714
1715
1716
1717
1718
1719
1720
1721
1722
1723
1724
1725
1726
1727
1728
1729
1730
1731
1732
1733
1734
1735
1736
1737
1738
1739
1740
1741
1742
1743
1744
1745
1746
1747
1748
1749
1750
1751
1752
1753
1754
1755
1756
1757
1758
1759
1760
1761
1762
1763
1764
1765
1766
1767
1768
1769
1770
1771
1772
1773
1774
1775
1776
1777
1778
1779
1780
1781
1782
1783
1784
1785
1786
1787
1788
1789
1790
1791
1792
1793
1794
1795
1796
1797
1798
1799
1800
1801
1802
1803
1804
1805
1806
1807
1808
1809
1810
1811
1812
1813
1814
1815
1816
1817
1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
1828
1829
1830
1831
1832
1833
1834
1835
1836
1837
1838
1839
1840
1841
1842
1843
1844
1845
1846
1847
1848
1849
1850
1851
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
1866
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
1888
1889
1890
1891
1892
1893
1894
1895
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
2051
2052
2053
2054
2055
2056
2057
2058
2059
2060
2061
2062
2063
2064
2065
2066
2067
2068
2069
2070
2071
2072
2073
2074
2075
2076
2077
2078
2079
2080
2081
2082
2083
2084
2085
2086
2087
2088
2089
2090
2091
2092
2093
2094
2095
2096
2097
2098
2099
2100
2101
2102
2103
2104
2105
2106
2107
2108
2109
2110
2111
2112
2113
2114
2115
2116
2117
2118
2119
2120
2121
2122
2123
2124
2125
2126
2127
2128
2129
2130
2131
2132
2133
2134
2135
2136
2137
2138
2139
2140
2141
2142
2143
2144
2145
2146
2147
2148
2149
2150
2151
2152
2153
2154
2155
2156
2157
2158
2159
2160
2161
2162
2163
2164
2165
2166
2167
2168
2169
2170
2171
2172
2173
2174
2175
2176
2177
2178
2179
2180
2181
2182
2183
2184
2185
2186
2187
2188
2189
2190
2191
2192
2193
2194
2195
2196
2197
2198
2199
2200
2201
2202
2203
2204
2205
2206
2207
2208
2209
2210
2211
2212
2213
2214
2215
2216
2217
2218
2219
2220
2221
2222
2223
2224
2225
2226
2227
2228
2229
2230
2231
2232
2233
2234
2235
2236
2237
2238
2239
2240
2241
2242
2243
2244
2245
2246
2247
2248
2249
2250
2251
2252
2253
2254
2255
2256
2257
2258
2259
2260
2261
2262
2263
2264
2265
2266
2267
2268
2269
2270
2271
2272
2273
2274
2275
2276
2277
2278
2279
2280
2281
2282
2283
2284
2285
2286
2287
2288
2289
2290
2291
2292
2293
2294
2295
2296
2297
2298
2299
2300
2301
2302
2303
2304
2305
2306
2307
2308
2309
2310
2311
2312
2313
2314
2315
2316
2317
2318
2319
2320
2321
2322
2323
2324
2325
2326
2327
2328
2329
2330
2331
2332
2333
2334
2335
2336
2337
2338
2339
2340
2341
2342
2343
2344
2345
2346
2347
2348
2349
2350
2351
2352
2353
2354
2355
2356
2357
2358
2359
2360
2361
2362
2363
2364
2365
2366
2367
2368
2369
2370
2371
2372
2373
2374
2375
2376
2377
2378
2379
2380
2381
2382
2383
2384
2385
2386
2387
2388
2389
2390
2391
2392
2393
2394
2395
2396
2397
2398
2399
2400
2401
2402
2403
2404
2405
2406
2407
2408
2409
2410
2411
2412
2413
2414
2415
2416
2417
2418
2419
2420
2421
2422
2423
2424
2425
2426
2427
2428
2429
2430
2431
2432
2433
2434
2435
2436
2437
2438
2439
2440
2441
2442
2443
2444
2445
2446
2447
2448
2449
2450
2451
2452
2453
2454
2455
2456
2457
2458
2459
2460
2461
2462
2463
2464
2465
2466
2467
2468
2469
2470
2471
2472
2473
2474
2475
2476
2477
2478
2479
2480
2481
2482
2483
2484
2485
2486
2487
2488
2489
2490
2491
2492
2493
2494
2495
2496
2497
2498
2499
2500
2501
2502
2503
2504
2505
2506
2507
2508
2509
2510
2511
2512
2513
2514
2515
2516
2517
2518
2519
2520
2521
2522
2523
2524
2525
2526
2527
2528
2529
2530
2531
2532
2533
2534
2535
2536
2537
2538
2539
2540
2541
2542
2543
2544
2545
2546
2547
2548
2549
2550
2551
2552
2553
2554
2555
2556
2557
2558
2559
2560
2561
2562
2563
2564
2565
2566
2567
2568
2569
2570
2571
2572
2573
2574
2575
2576
2577
2578
2579
2580
2581
2582
2583
2584
2585
2586
2587
2588
2589
2590
2591
2592
2593
2594
2595
2596
2597
2598
2599
2600
2601
2602
2603
2604
2605
2606
2607
2608
2609
2610
2611
2612
2613
2614
2615
2616
2617
2618
2619
2620
2621
2622
2623
2624
2625
2626
2627
2628
2629
2630
2631
2632
2633
2634
2635
2636
2637
2638
2639
2640
2641
2642
2643
2644
2645
2646
2647
2648
2649
2650
2651
2652
2653
2654
2655
2656
2657
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
2671
2672
2673
2674
2675
2676
2677
2678
2679
2680
2681
2682
2683
2684
2685
2686
2687
2688
2689
2690
2691
2692
2693
2694
2695
2696
2697
2698
2699
2700
2701
2702
2703
2704
2705
2706
2707
2708
2709
2710
2711
2712
2713
2714
2715
2716
2717
2718
2719
2720
2721
2722
2723
2724
2725
2726
2727
2728
2729
2730
2731
2732
2733
2734
2735
2736
2737
2738
2739
2740
2741
2742
2743
2744
2745
2746
2747
2748
2749
2750
2751
2752
2753
2754
2755
2756
2757
2758
2759
2760
2761
2762
2763
2764
2765
2766
2767
2768
2769
2770
2771
2772
2773
2774
2775
2776
2777
2778
2779
2780
2781
2782
2783
2784
2785
2786
2787
2788
2789
2790
2791
2792
2793
2794
2795
2796
2797
2798
2799
2800
2801
2802
2803
2804
2805
2806
2807
2808
2809
2810
2811
2812
2813
2814
2815
2816
2817
2818
2819
2820
2821
2822
2823
2824
2825
2826
2827
2828
2829
2830
2831
2832
2833
2834
2835
2836
2837
2838
2839
2840
2841
2842
2843
2844
2845
2846
2847
2848
2849
2850
2851
2852
2853
2854
2855
2856
2857
2858
2859
2860
2861
2862
2863
2864
2865
2866
2867
2868
2869
2870
2871
2872
2873
2874
2875
2876
2877
2878
2879
2880
2881
2882
2883
2884
2885
2886
2887
2888
2889
2890
2891
2892
2893
2894
2895
2896
2897
2898
2899
2900
2901
2902
2903
2904
2905
2906
2907
2908
2909
2910
2911
2912
2913
2914
2915
2916
2917
2918
2919
2920
2921
2922
2923
2924
2925
2926
2927
2928
2929
2930
2931
2932
2933
2934
2935
2936
2937
2938
2939
2940
2941
2942
2943
2944
2945
2946
2947
2948
2949
2950
2951
2952
2953
2954
2955
2956
2957
2958
2959
2960
2961
2962
2963
2964
2965
2966
2967
2968
2969
2970
2971
2972
2973
2974
2975
2976
2977
2978
2979
2980
2981
2982
2983
2984
2985
2986
2987
2988
2989
2990
2991
2992
2993
2994
2995
2996
2997
2998
2999
3000
3001
3002
3003
3004
3005
3006
3007
3008
3009
3010
3011
3012
3013
3014
3015
3016
3017
3018
3019
3020
3021
3022
3023
3024
3025
3026
3027
3028
3029
3030
3031
3032
3033
3034
3035
3036
3037
3038
3039
3040
3041
3042
3043
3044
3045
3046
3047
3048
3049
3050
3051
3052
3053
3054
3055
3056
3057
3058
3059
3060
3061
3062
3063
3064
3065
3066
3067
3068
3069
3070
3071
3072
3073
3074
3075
3076
3077
3078
3079
3080
3081
3082
3083
3084
3085
3086
3087
3088
3089
3090
3091
3092
3093
3094
3095
3096
3097
3098
3099
3100
3101
3102
3103
3104
3105
3106
3107
3108
3109
3110
3111
3112
3113
3114
3115
3116
3117
3118
3119
3120
3121
3122
3123
3124
3125
3126
3127
3128
3129
3130
3131
3132
3133
3134
3135
3136
3137
3138
3139
3140
3141
3142
3143
3144
3145
3146
3147
3148
3149
3150
3151
3152
3153
3154
3155
3156
3157
3158
3159
3160
3161
3162
3163
3164
3165
3166
3167
3168
3169
3170
3171
3172
3173
3174
3175
3176
3177
3178
3179
3180
3181
3182
3183
3184
3185
3186
3187
3188
3189
3190
3191
3192
3193
3194
3195
3196
3197
3198
3199
3200
3201
3202
3203
3204
3205
3206
3207
3208
3209
3210
3211
3212
3213
3214
3215
3216
3217
3218
3219
3220
3221
3222
3223
3224
3225
3226
3227
3228
3229
3230
3231
3232
3233
3234
3235
3236
3237
3238
3239
3240
3241
3242
3243
3244
3245
3246
3247
3248
3249
3250
3251
3252
3253
3254
3255
3256
3257
3258
3259
3260
3261
3262
3263
3264
3265
3266
3267
3268
3269
3270
3271
3272
3273
3274
3275
3276
3277
3278
3279
3280
3281
3282
3283
3284
3285
3286
3287
3288
3289
3290
3291
3292
3293
3294
3295
3296
3297
3298
3299
3300
3301
3302
3303
3304
3305
3306
3307
3308
3309
3310
3311
3312
3313
3314
3315
3316
3317
3318
3319
3320
3321
3322
3323
3324
3325
3326
3327
3328
3329
3330
3331
3332
3333
3334
3335
3336
3337
3338
3339
3340
3341
3342
3343
3344
3345
3346
3347
3348
3349
3350
3351
3352
3353
3354
3355
3356
3357
3358
3359
3360
3361
3362
3363
3364
3365
3366
3367
3368
3369
3370
3371
3372
3373
3374
3375
3376
3377
3378
3379
3380
3381
3382
3383
3384
3385
3386
3387
3388
3389
3390
3391
3392
3393
3394
3395
3396
3397
3398
3399
3400
3401
3402
3403
3404
3405
3406
3407
3408
3409
3410
3411
3412
3413
3414
3415
3416
3417
3418
3419
3420
3421
3422
3423
3424
3425
3426
3427
3428
3429
3430
3431
3432
3433
3434
3435
3436
3437
3438
3439
3440
3441
3442
3443
3444
3445
3446
3447
3448
3449
3450
3451
3452
3453
3454
3455
3456
3457
3458
3459
3460
3461
3462
3463
3464
3465
3466
3467
3468
3469
3470
3471
3472
3473
3474
3475
3476
3477
3478
3479
3480
3481
3482
3483
3484
3485
3486
3487
3488
3489
3490
3491
3492
3493
3494
3495
3496
3497
3498
3499
3500
3501
3502
3503
3504
3505
3506
3507
3508
3509
3510
3511
3512
3513
3514
3515
3516
3517
3518
3519
3520
3521
3522
3523
3524
3525
3526
3527
3528
3529
3530
3531
3532
3533
3534
3535
3536
3537
3538
3539
3540
3541
3542
3543
3544
3545
3546
3547
3548
3549
3550
3551
3552
3553
3554
3555
3556
3557
3558
3559
3560
3561
3562
3563
3564
3565
3566
3567
3568
3569
3570
3571
3572
3573
3574
3575
3576
3577
3578
3579
3580
3581
3582
3583
3584
3585
3586
3587
3588
3589
3590
3591
3592
3593
3594
3595
3596
3597
3598
3599
3600
3601
3602
3603
3604
3605
3606
3607
3608
3609
3610
3611
3612
3613
3614
3615
3616
3617
3618
3619
3620
3621
3622
3623
3624
3625
3626
3627
3628
3629
3630
3631
3632
3633
3634
3635
3636
3637
3638
3639
3640
3641
3642
3643
3644
3645
3646
3647
3648
3649
3650
3651
3652
3653
3654
3655
3656
3657
3658
3659
3660
3661
3662
3663
3664
3665
3666
3667
3668
3669
3670
3671
3672
3673
3674
3675
3676
3677
3678
3679
3680
3681
3682
3683
3684
3685
3686
3687
3688
3689
3690
3691
3692
3693
3694
3695
3696
3697
3698
3699
3700
3701
3702
3703
3704
3705
3706
3707
3708
3709
3710
3711
3712
3713
3714
3715
3716
3717
3718
3719
3720
3721
3722
3723
3724
3725
3726
3727
3728
3729
3730
3731
3732
3733
3734
3735
3736
3737
3738
3739
3740
3741
3742
3743
3744
3745
3746
3747
3748
3749
3750
3751
3752
3753
3754
3755
3756
3757
3758
3759
3760
3761
3762
3763
3764
3765
3766
3767
3768
3769
3770
3771
3772
3773
3774
3775
3776
3777
3778
3779
3780
3781
3782
3783
3784
3785
3786
3787
3788
3789
3790
3791
3792
3793
3794
3795
3796
3797
3798
3799
3800
3801
3802
3803
3804
3805
3806
3807
3808
3809
3810
3811
3812
3813
3814
3815
3816
3817
3818
3819
3820
3821
3822
3823
3824
3825
3826
3827
3828
3829
3830
3831
3832
3833
3834
3835
3836
3837
3838
3839
3840
3841
3842
3843
3844
3845
3846
3847
3848
3849
3850
3851
3852
3853
3854
3855
3856
3857
3858
3859
3860
3861
3862
3863
3864
3865
3866
3867
3868
3869
3870
3871
3872
3873
3874
3875
3876
3877
3878
3879
3880
3881
3882
3883
3884
3885
3886
3887
3888
3889
3890
3891
3892
3893
3894
3895
3896
3897
3898
3899
3900
3901
3902
3903
3904
3905
3906
3907
3908
3909
3910
3911
3912
3913
3914
3915
3916
3917
3918
3919
3920
3921
3922
3923
3924
3925
3926
3927
3928
3929
3930
3931
3932
3933
3934
3935
3936
3937
3938
3939
3940
3941
3942
3943
3944
3945
3946
3947
3948
3949
3950
3951
3952
3953
3954
3955
3956
3957
3958
3959
3960
3961
3962
3963
3964
3965
3966
3967
3968
3969
3970
3971
3972
3973
3974
3975
3976
3977
3978
3979
3980
3981
3982
3983
3984
3985
3986
3987
3988
3989
3990
3991
3992
3993
3994
3995
3996
3997
3998
3999
4000
4001
4002
4003
4004
4005
4006
4007
4008
4009
4010
4011
4012
4013
4014
4015
4016
4017
4018
4019
4020
4021
4022
4023
4024
4025
4026
4027
4028
4029
4030
4031
4032
4033
4034
4035
4036
4037
4038
4039
4040
4041
4042
4043
4044
4045
4046
4047
4048
4049
4050
4051
4052
4053
4054
4055
4056
4057
4058
4059
4060
4061
4062
4063
4064
4065
4066
4067
4068
4069
4070
4071
4072
4073
4074
4075
4076
4077
4078
4079
4080
4081
4082
4083
4084
4085
4086
4087
4088
4089
4090
4091
4092
4093
4094
4095
4096
4097
4098
4099
4100
4101
4102
4103
4104
4105
4106
4107
4108
4109
4110
4111
4112
4113
4114
4115
4116
4117
4118
4119
4120
4121
4122
4123
4124
4125
4126
4127
4128
4129
4130
4131
4132
4133
4134
4135
4136
4137
4138
4139
4140
4141
4142
4143
4144
4145
4146
4147
4148
4149
4150
4151
4152
4153
4154
4155
4156
4157
4158
4159
4160
4161
4162
4163
4164
4165
4166
4167
4168
4169
4170
4171
4172
4173
4174
4175
4176
4177
4178
4179
4180
4181
4182
4183
4184
4185
4186
4187
4188
4189
4190
4191
4192
4193
4194
4195
4196
4197
4198
4199
4200
4201
4202
4203
4204
4205
4206
4207
4208
4209
4210
4211
4212
4213
4214
4215
4216
4217
4218
4219
4220
4221
4222
4223
4224
4225
4226
4227
4228
4229
4230
4231
4232
4233
4234
4235
4236
4237
4238
4239
4240
4241
4242
4243
4244
4245
4246
4247
4248
4249
4250
4251
4252
4253
4254
4255
4256
4257
4258
4259
4260
4261
4262
4263
4264
4265
4266
4267
4268
4269
4270
4271
4272
4273
4274
4275
4276
4277
4278
4279
4280
4281
4282
4283
4284
4285
4286
4287
4288
4289
4290
4291
4292
4293
4294
4295
4296
4297
4298
4299
4300
4301
4302
4303
4304
4305
4306
4307
4308
4309
4310
4311
4312
4313
4314
4315
4316
4317
4318
4319
4320
4321
4322
4323
4324
4325
4326
4327
4328
4329
4330
4331
4332
4333
4334
4335
4336
4337
4338
4339
4340
4341
4342
4343
4344
4345
4346
4347
4348
4349
4350
4351
4352
4353
4354
4355
4356
4357
4358
4359
4360
4361
4362
4363
4364
4365
4366
4367
4368
4369
4370
4371
4372
4373
4374
4375
4376
4377
4378
4379
4380
4381
4382
4383
4384
4385
4386
4387
4388
4389
4390
4391
4392
4393
4394
4395
4396
4397
4398
4399
[
    {
        "question": ": The term used to describe solutions where AI agents  participate in conversations with humans. Choose t he correct option.",
        "options": [
            "A. Machine Learning",
            "B. Natural language processing",
            "C. Conversational AI",
            "D. All of the above"
        ],
        "correct": "C. Conversational AI",
        "explanation": "Explanation Conversational AI is the term used to d escribe solutions where AI agents participate in conversations with humans. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/get-started-ai-fundamentals/6- understand- conversational-ai",
        "references": ""
    },
    {
        "question": ": Bots can be the basis of AI solutions such as below  applications. Choose the correct options.",
        "options": [
            "A. Customer support for products or services",
            "B. Automatically translate spoken or written phrases  between languages",
            "C. Health care consultations and self-diagnosis",
            "D. Home automation and personal digital assistants"
        ],
        "correct": "",
        "explanation": "Explanation Bots can be the basis of AI solutions f or: Customer support for products or services. Rese rvation systems for restaurants, airlines, cinemas, and other appointme nt based businesses. Health care consultations and self- diagnosis. Home automation and personal digital assistants. Referen ce Link: https://docs.microsoft.com/en-us/learn/mod ules/ get-started-ai- fundamentals/6-understand-conversational-ai",
        "references": ""
    },
    {
        "question": ": Most commonly, ___________ solutions use bots to ma nage dialogs with users.",
        "options": [
            "A. Conversational AI",
            "B. Computer Vision",
            "C. Custom Vision",
            "D. Natural language processing Correct Answer: A"
        ],
        "correct": "",
        "explanation": "Explanation Most commonly, conversational AI soluti ons use bots to manage dialogs with users. Referenc e Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/6-understand-conversational -ai",
        "references": ""
    },
    {
        "question": ": User can use the following services to create conve rsational AI solutions on Microsoft Azure. Choose t he correct options.",
        "options": [
            "A. QnA Maker",
            "B. Face API",
            "C. Azure Bot Service",
            "D. Text Translate"
        ],
        "correct": "",
        "explanation": "Explanation User can use QnA Maker & Azure Bot Serv ice service to create conversational AI solutions o n Microsoft Azure. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/get-started-ai-fundamentals/6- understand- conversational-ai",
        "references": ""
    },
    {
        "question": ": Which cognitive service enables you to quickly buil d a knowledge base of questions and answers that ca n form the basis of a dialog between a human and an AI agent?",
        "options": [
            "A. Azure Bot",
            "B. QnA Maker",
            "C. Texmaker",
            "D. None of the above"
        ],
        "correct": "B. QnA Maker",
        "explanation": "Explanation QnA Maker cognitive service enables you  to quickly build a knowledge base of questions and answers that can form the basis of a dialog between a human and an A I agent. Reference Link: https://docs.microsoft.com /en- us/learn/modules/get-started-ai-fundamentals/6-unde rstand-conversational-ai",
        "references": ""
    },
    {
        "question": "Which service provides a platform for creating, pub lishing, and managing bots?",
        "options": [
            "A. Azure Bot",
            "B. QnA Maker",
            "C. Texmaker",
            "D. Azure ChatBot"
        ],
        "correct": "A. Azure Bot",
        "explanation": "Explanation Azure Bot service provides a platform f or creating, publishing, and managing bots. Referen ce Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/6-understand-conversational -ai",
        "references": ""
    },
    {
        "question": ": Developers can use the ____________ to create a bot  and manage it with Azure Bot Service - integrating  back- end services like QnA Maker and LUIS, and connecting to  channels for web chat, email, Microsoft Teams, and others.",
        "options": [
            "A. ChatBot Framework",
            "B. Bot Framework",
            "C. QnA Maker framework",
            "D. All of the above"
        ],
        "correct": "B. Bot Framework",
        "explanation": "Explanation Developers can use the Bot Framework to  create a bot and manage it with Azure Bot Service - integrating back- end services like QnA Maker and LUIS, and connectin g to channels for web chat, email, Microsoft Teams,  and others. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/6-understan d- conversational-ai",
        "references": ""
    },
    {
        "question": ": What all potential challenges risks are faced by an  AI application developer? Choose the correct optio ns.",
        "options": [
            "A. Errors may cause harm",
            "B. Solutions may work for everyone",
            "C. Who's not liable for AI-driven decisions?",
            "D. Data could be exposed"
        ],
        "correct": "",
        "explanation": "Explanation The following table shows some of the p otential challenges risks facing an AI application developer. Bias can affect results Errors may cause harm Data could be exposed Solutions may not work for everyone Users m ust trust a complex system Who's liable for AI-driven decisions ? Reference Link: https://docs.microsoft.com/en-us/ learn/ modules/get- started-ai-fundamentals/7-challenges-with-ai",
        "references": ""
    },
    {
        "question": ": Which Microsoft bot is built on Azure Bot Service a nd enables developers to quickly create conversatio nal AI solutions for health care?",
        "options": [
            "A. Microsoft healthManagement bot",
            "B. Microsoft healthcare bot",
            "C. Microsoft health bot",
            "D. Microsoft healthCure bot"
        ],
        "correct": "B. Microsoft healthcare bot",
        "explanation": "Explanation The Microsoft healthcare bot is built o n Azure Bot Service and enables developers to quick ly create conversational AI solutions for health care. To see  an example of the healthcare bot:https://www.microsoft.com/research/project/heal th-bot/ Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/6-understan d- conversational-ai",
        "references": ""
    },
    {
        "question": ": An autonomous vehicle experiences a system failure and causes a collision. Under which AI challenge th e following example is categorized.",
        "options": [
            "A. Data could be exposed",
            "B. Bias can affect results",
            "C. Errors may cause harm",
            "D. Users must trust a complex system"
        ],
        "correct": "C. Errors may cause harm",
        "explanation": "Explanation Errors may cause harm - An autonomous v ehicle experiences a system failure and causes a collision Reference Link: https://docs.microsoft.com/en-us/learn/module s/get-started-ai-fundamentals/7-challenges-with-ai",
        "references": ""
    },
    {
        "question": ": The fraction of the cases classified as positive th at are actually positive (the number of true positi ves divided by the number of true positives plus false negatives). Cho ose the correct option.",
        "options": [
            "A. Precision",
            "B. F1 Score",
            "C. Accuracy",
            "D. Recall"
        ],
        "correct": "D. Recall",
        "explanation": "Explanation Recall: The fraction of the cases class ified as positive that are actually positive (the n umber of true positives divided by the number of true positives plus false negatives). In other words, out of all the patients  who actually have diabetes, how many did the model identify? Referenc e Link: https://docs.microsoft.com/en-us/learn/modu les/ create- classification-model-azure-machine-learning-designe r/evaluate-model",
        "references": ""
    },
    {
        "question": ": In the case of this binary classification model, th e predicted probability for a negative prediction i s a value between 0 and 1.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation In the case of this binary classificati on model, the predicted probability for a positive prediction is a value between 0 and 1. Reference Link: https://docs.micro soft.com/en-us/learn/modules/create-classification- model- azure- machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": ROC stands for _______________.",
        "options": [
            "A. Receiver operating characteristic",
            "B. Receiving operator characteristic",
            "C. Retransmitting operator characteristic",
            "D. None of the above"
        ],
        "correct": "A. Receiver operating characteristic",
        "explanation": "Explanation Explanation ROC stands for receiver operating chara cteristic. Reference Link: https://docs.microsoft.c om/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": If the pipeline does not include _________ and ____ ___ modules, go back to the Designer page and then re- open the inference pipeline.",
        "options": [
            "A. Web Service Output",
            "B. Service Output Features",
            "C. Web Service Input",
            "D. Service Features Input"
        ],
        "correct": "",
        "explanation": "Explanation If the pipeline does not include Web Se rvice Input and Web Service Output modules, go back  to the Designer page and then re-open the inference pipeline. Refer ence Link: https://docs.microsoft.com/en-us/learn/m odules/ create- classification-model-azure-machine-learning-designe r/inference-pipeline",
        "references": ""
    },
    {
        "question": ": Your inference pipeline predicts whether or not pat ients are at risk for diabetes based on their featu res.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Your inference pipeline predicts whethe r or not patients are at risk for diabetes based on  their features. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-classification-model-azure-machi ne- learning- designer/inference-pipeline",
        "references": ""
    },
    {
        "question": ": In which classification model, the predicted probab ility for a positive prediction is a value between 0 and 1?",
        "options": [
            "A. Binary classification model",
            "B. Nominal classification model",
            "C. Multinominal classification model",
            "D. Multi-class classification model"
        ],
        "correct": "A. Binary classification model",
        "explanation": "Explanation In the case of this binary classificati on model, the predicted probability for a positive prediction is a value between 0 and 1. Reference Link: https://docs.micro soft.com/en-us/learn/modules/create-classification- model- azure- machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": You are using Azure Machine Learning designer to cr eate a training pipeline for a binary classificatio n model. You have added a dataset containing features and labels , a Two-Class Decision Forest module, and a Train M odel module. You plan to use Score Model and Evaluate Mo del modules to test the trained model with a subset  of the dataset that was not used for training. Which addit ional kind of module should you add?",
        "options": [
            "A. Join Data",
            "B. Split Data",
            "C. Select Columns in Dataset",
            "D. None of the above"
        ],
        "correct": "B. Split Data",
        "explanation": "Explanation Use a Split Data module to randomly spl it a dataset into training and validation subsets. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ inference- pipeline",
        "references": ""
    },
    {
        "question": ": You use an Azure Machine Learning designer pipeline  to train and test a binary classification model. Y ou review the model's performance metrics in an Evaluate Model mo dule, and note that it has an AUC score of 0.3. Wha t can you conclude about the model?",
        "options": [
            "A. The model can explain 30% of the variance between  true and predicted labels.",
            "B. The model predicts accurately for 70% of test cas es.",
            "C. The model performs worse than random guessing.",
            "D. All of the above"
        ],
        "correct": "C. The model performs worse than random guessing.",
        "explanation": "Explanation An AUC of 0.5 is what you'd expect with  random prediction of a binary model. Reference Lin k: https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ inference- pipeline",
        "references": ""
    },
    {
        "question": ": A form of machine learning that is used to group si milar items into clusters based on their features. Choose the correct option.",
        "options": [
            "A. Time series forecasting",
            "B. Clustering",
            "C. Classification",
            "D. Regression"
        ],
        "correct": "",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": A researcher might take measurements of penguins, a nd group them based on similarities in their propor tions. Choose the correct option.",
        "options": [
            "A. Classification",
            "B. Regression",
            "C. Time series forecasting",
            "D. Clustering"
        ],
        "correct": "D. Clustering",
        "explanation": "Explanation Clustering is a form of machine learnin g that is used to group similar items into clusters  based on their features. For example, a researcher might take measurements o f penguins, and group them based on similarities in  their proportions. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-clustering-model-azure-machine- learning- designer/introduction",
        "references": ""
    },
    {
        "question": ": Choose the metrics used for clustering from the fol lowing.",
        "options": [
            "A. Average Distance to Other Center",
            "B. Number of Edges",
            "C. Average Distance to Cluster Center D. Number of Points"
        ],
        "correct": "",
        "explanation": "Explanation The metrics used for clustering are as following: Average Distance to Other Center, Averag e Distance to Cluster Center, Number of Points, Maximal Distance to Cluster Center. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": Evaluating a clustering model is made difficult by the fact that there are no previously known true va lues for the cluster assignments.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Evaluating a clustering model is made d ifficult by the fact that there are no previously k nown true values for the cluster assignments. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/create-clustering- model- azure- machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": To create clustering models by using a drag and dro p visual interface, without needing to write any co de. Choose the correct option.",
        "options": [
            "A. Azure Machine Learning Studio",
            "B. Azure Machine Learning designer",
            "C. Microsoft Azure Machine Learning dashboard",
            "D. None of the above",
            "A. Average Distance to Other Center",
            "B. Average Distance to Cluster Center",
            "C. Number of Edges",
            "D. Number of Points"
        ],
        "correct": "A. Average Distance to Other Center",
        "explanation": "Explanation Average Distance to Other Center: This indicates how close, on average, each point in the cluster is to the centroids of all other clusters. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/create - clustering-model- azure-machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": It is an example of __________, in which you train a model to separate items into clusters based purel y on their characteristics, or features.",
        "options": [
            "A. Semi-supervised machine learning",
            "B. Supervised machine learning",
            "C. Unsupervised machine learning",
            "D. All of the above"
        ],
        "correct": "C. Unsupervised machine learning",
        "explanation": "Explanation Clustering is an example of unsupervise d machine learning, in which you train a model to s eparate items into clusters based purely on their characteristics, or features. There is no previously known cluster valu e (or label) from which to train the model. Reference Link: https://docs.mi crosoft.com/en-us/learn/modules/create-clustering-m odel- azure-machine- learning-designer/introduction",
        "references": ""
    },
    {
        "question": ": You use Azure Machine Learning designer to create a  training pipeline for a classification model. What  must you do before deploying the model as a service?",
        "options": [
            "A. Create an inference pipeline from the training pi peline",
            "B. Add an Evaluate Model module to the training pipe line",
            "C. Clone the training pipeline with a different name",
            "D. None of the above Correct Answer: A"
        ],
        "correct": "",
        "explanation": "Explanation You must create an inference pipeline t o deploy as a service. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/inference-pipeline",
        "references": ""
    },
    {
        "question": ": You train an image classification model that achiev es less than satisfactory evaluation metrics. How m ight you improve it?",
        "options": [
            "A. Reduce the size of the images used to train the m odel.",
            "B. Add a new label for \"unknown\" classes.",
            "C. Add more images to the training set.",
            "D. All of the above"
        ],
        "correct": "C. Add more images to the training set.",
        "explanation": "Explanation Generally, adding more images to the pr oject an retraining the model is likely to improve performance. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/classify-images-custom-vision/2-azure-i mage- classification",
        "references": ""
    },
    {
        "question": ": Which of the following results does an object detec tion model typically return for an image?",
        "options": [
            "A. A class label and probability score for the image",
            "B. Bounding box coordinates that indicate the region  of the image where all of the objects it",
            "C. A class label, probability, and bounding box for each object in the image",
            "D. None of the above"
        ],
        "correct": "C. A class label, probability, and bounding box for each object in the image",
        "explanation": "Explanation An object detection model predicts a cl ass label, probability, and bounding box for each o bject in the image. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/detect-objects-images-custom-vision/1a- what- is-object- detection/",
        "references": ""
    },
    {
        "question": ": You have published an image classification model. W hat information must you provide to developers who want to use it?",
        "options": [
            "A. Only the project ID.",
            "B. The project ID, the model name, and the key and e ndpoint for the prediction resource",
            "C. The project ID, iteration number, and the key and  endpoint for the training resource.",
            "D. None of the above"
        ],
        "correct": "B. The project ID, the model name, and the key and e ndpoint for the prediction resource",
        "explanation": "Explanation To use a published model, you need the project ID, the model name, and the key and endpoin t for the prediction resource. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/classify-images-custom-vision /2- azure-image- classification",
        "references": ""
    },
    {
        "question": ": You can use the Custom Vision cognitive service to train an image classification model based on existi ng images.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Yes, you can use the Custom Vision cogn itive service to train an image classification mode l based on existing images. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/classify-images-custom-vision/2 - azure-image- classification",
        "references": ""
    },
    {
        "question": ": Which workload is used for identifying key infrastr ucture for major disaster preparation efforts?",
        "options": [
            "A. Image analysis",
            "B. Image processing",
            "C. Image classification",
            "D. Image manipulation"
        ],
        "correct": "C. Image classification",
        "explanation": "Explanation Disaster investigation: identifying key  infrastructure for major disaster preparation effo rts. For example, identifying bridges and roads in aerial images can help disaster relief teams plan ahead in regions th at are not well mapped. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/classify-images-custom-vision/1-introdu ction",
        "references": ""
    },
    {
        "question": ": You plan to use a set of images to train an object detection model, and then publish the model as a pr edictive service. You want to use a single Azure resource with the sa me key and endpoint for training and prediction. Wh at kind of Azure resource should you create?",
        "options": [
            "A. Cognitive Services",
            "B. Custom Vision",
            "C. Computer Vision",
            "D. All of the above"
        ],
        "correct": "A. Cognitive Services",
        "explanation": "Explanation A cognitive services resource can be us ed for both training and prediction. Reference Link : https://docs.microsoft.com/en-us/learn/modules/dete ct-objects-images-custom-vision/1a-what-is-object- detection/",
        "references": ""
    },
    {
        "question": ": What percentage of class predictions did the model correctly identify? Choose the correct evaluation m etrics for given example.",
        "options": [
            "A. Precision",
            "B. Mean Absolute Error(MAE)",
            "C. Recall",
            "D. Average Precision (AP)"
        ],
        "correct": "C. Recall",
        "explanation": "Explanation Recall identifies what percentage of cl ass predictions did the model correctly identify. R eference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
        "references": ""
    },
    {
        "question": ": The Computer Vision service can not generate thumbn ails.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation The Computer Vision service can generat e thumbnails like creating small versions of images . Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": You want to use the Language service to determine t he key talking points in a text document. Which fea ture of the service should you use?",
        "options": [
            "A. Sentiment analysis",
            "B. Key phrase extraction",
            "C. Entity detection",
            "D. All of the above"
        ],
        "correct": "B. Key phrase extraction",
        "explanation": "Explanation Key phrases can be used to identify the  main talking points in a text document. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/3-exercise",
        "references": ""
    },
    {
        "question": ": You plan to build an application that uses the Spee ch service to transcribe audio recordings of phone calls into text, and then submits the transcribed text to the Text A nalytics service to extract key phrases. You want t o manage access and billing for the application services in a singl e Azure resource. Which type of Azure resource shou ld you create?",
        "options": [
            "A. Speech",
            "B. Text Analytics",
            "C. Cognitive Services",
            "D. None of the above"
        ],
        "correct": "C. Cognitive Services",
        "explanation": "Explanation This resource would support both the Sp eech and Text Analytics services. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
        "references": ""
    },
    {
        "question": ": You can use NLP to build solutions that extracting _________ from text or speech, or that formulate __ _____ in natural language.",
        "options": [
            "A. Meaningful responses",
            "B. Language meaning C. Meaningful requests",
            "D. Semantic meaning"
        ],
        "correct": "",
        "explanation": "Explanation You can use NLP to build solutions that  extracting semantic meaning from text or speech, o r that formulate meaningful responses in natural language. Reference  Link: https://docs.microsoft.com/en-in/learn/modul es/ analyze-text- with-text-analytics-service/3-exercise",
        "references": ""
    },
    {
        "question": ": Which model converts the audio signal into phonemes ?",
        "options": [
            "A. An acoustic model",
            "B. A Speech model",
            "C. A language model",
            "D. An object model"
        ],
        "correct": "A. An acoustic model",
        "explanation": "Explanation An acoustic model that converts the aud io signal into phonemes (representations of specifi c sounds). Reference Link: https://docs.microsoft.com/en-in/learn/module s/recognize-synthesize-speech/1-introduction/",
        "references": ""
    },
    {
        "question": ": Which model maps phonemes to words, usually using a  statistical algorithm that predicts the most proba ble sequence of words based on the phonemes?",
        "options": [
            "A. An acoustic model",
            "B. A Speech model",
            "C. A language model",
            "D. An object model"
        ],
        "correct": "C. A language model",
        "explanation": "Explanation A language model that maps phonemes to words, usually using a statistical algorithm that p redicts the most probable sequence of words based on the phonemes. R eference Link: https://docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
        "references": ""
    },
    {
        "question": "You want to use the Speech service to build an appl ication that reads incoming email message subjects aloud. Which API should you use?",
        "options": [
            "A. Speech-to-Text",
            "B. Text-to-Speech",
            "C. Translate",
            "D. None of the above"
        ],
        "correct": "B. Text-to-Speech",
        "explanation": "Explanation The Text-to-Speech API converts text to  audible speech. Reference Link: https:// docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
        "references": ""
    },
    {
        "question": ": When might you see NaN returned for a score in Lang uage Detection?",
        "options": [
            "A. When the score calculated by the service is outsi de the range of 0 to 1",
            "B. When the predominant language in the text is mixe d with other languages",
            "C. When the language is ambiguous",
            "D. All of the above"
        ],
        "correct": "C. When the language is ambiguous",
        "explanation": "Explanation The service will return NaN when it can not determine the language in the provided text. Re ference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/3-exercise",
        "references": ""
    },
    {
        "question": ": Natural Language Processing (NLP) is a branch of ar tificial intelligence (AI) that deals with ______ &  ________ language.",
        "options": [
            "A. Written",
            "B. Spoken",
            "C. Reading",
            "D. Listening"
        ],
        "correct": "",
        "explanation": "Explanation Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that deals w ith written and spoken language. Reference Link: https://docs.microsoft.co m/en-in/learn/modules/analyze-text-with-text-analyt ics- service/3- exercise",
        "references": ""
    },
    {
        "question": ": What is concerned with taking the spoken word and c onverting it into data that can be processed - ofte n by transcribing it into a text representation?",
        "options": [
            "A. Speech recognition",
            "B. Voice recognition",
            "C. Text recognition",
            "D. Object recognition"
        ],
        "correct": "A. Speech recognition",
        "explanation": "Explanation Speech recognition is concerned with ta king the spoken word and converting it into data th at can be processed - often by transcribing it into a text representation . Reference Link: https://docs.microsoft.com/en-in/ learn/ modules/recognize- synthesize-speech/1-introduction/",
        "references": ""
    },
    {
        "question": ": It is concerned with vocalizing data, usually by co nverting text to speech. Choose the correct option.",
        "options": [
            "A. Speech recognition",
            "B. Speech synthesis",
            "C. Speech translation",
            "D. Speech analytics"
        ],
        "correct": "B. Speech synthesis",
        "explanation": "Explanation Speech synthesis is in many respects th e reverse of speech recognition. It is concerned wi th vocalizing data, usually by converting text to speech. Reference Lin k: https://docs.microsoft.com/en-in/learn/modules/r ecognize- synthesize- speech/1-introduction/",
        "references": ""
    },
    {
        "question": ": You use the Language service to perform sentiment a nalysis on a document, and a score of 0.99 is retur ned. What does this score indicate about the document sentime nt?",
        "options": [
            "A. The document is positive.",
            "B. The document is neutral.",
            "C. The document is negative. D. None of the above"
        ],
        "correct": "A. The document is positive.",
        "explanation": "Explanation Score values closer to 1 indicated a mo re positive sentiment where scores closer to 0 indi cated negative sentiment. Reference Link: https://docs.microsoft.c om/en-in/learn/modules/analyze-text-with-text-analy tics- service/3- exercise",
        "references": ""
    },
    {
        "question": ": We expect artificial intelligence (AI) solutions to  accept vocal commands and provide spoken responses . To enable this kind of interaction, the AI system must suppor t two capabilities? Choose the correct options.",
        "options": [
            "A. Speech recognition",
            "B. Speech synthesis",
            "C. Speech analysis",
            "D. All of the above"
        ],
        "correct": "",
        "explanation": "Explanation To enable this kind of interaction, the  AI system must support two capabilities: Speech re cognition - the ability to detect and interpret spoken input. Speech synthe sis - the ability to generate spoken output. Refere nce Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
        "references": ""
    },
    {
        "question": ": An example of something a user might say, and which  your application must interpret. Choose the correc t term.",
        "options": [
            "A. Entities",
            "B. Intents",
            "C. Utterances",
            "D. Objects"
        ],
        "correct": "C. Utterances",
        "explanation": "Explanation An utterance is an example of something  a user might say, and which your application must interpret. For example, when using a home automation system, a use r might use the following utterances.",
        "references": ""
    },
    {
        "question": ":You can control whether the short answer from the r esponse by using the __________ checkbox at the top  of the test pane.",
        "options": [
            "A. Display short answer",
            "B. Show short answer",
            "C. Present short answer",
            "D. None of the above"
        ],
        "correct": "A. Display short answer",
        "explanation": "Explanation You can control whether the short answe r from the response by using the Display short answ er checkbox at the top of the test pane. Reference Link: https://docs. microsoft.com/en-in/learn/modules/build-faq-chatbot -qna- maker-azure-bot- service/3-create-bot",
        "references": ""
    },
    {
        "question": ": The response includes a ________ as well as a more verbose _________.",
        "options": [
            "A. answer passage",
            "B. question passage",
            "C. long answer",
            "D. short answer"
        ],
        "correct": "",
        "explanation": "Explanation The response includes a short answer as  well as a more verbose answer passage. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/3-create- bot",
        "references": ""
    },
    {
        "question": ": The knowledge base provides a back-end service that  client applications can use to answer questions th rough some sort of user interface.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation The knowledge base provides a back-end service that client applications can use to answer questions through some sort of user interface. Reference Link: https: //docs.microsoft.com/en-in/learn/modules/build-faq- chatbot- qna-maker- azure-bot-service/3-create-bot",
        "references": ""
    },
    {
        "question": ": To access the knowledge base, client applications r equire following. Choose the correct option.",
        "options": [
            "A. The knowledge base ID",
            "B. The knowledge base Name",
            "C. The knowledge base endpoint",
            "D. The knowledge base authorization key"
        ],
        "correct": "",
        "explanation": "Explanation To access the knowledge base, client ap plications require: The knowledge base ID The knowl edge base endpoint The knowledge base authorization key Refer ence Link: https://docs.microsoft.com/en-in/learn/ modules/build-faq- chatbot-qna-maker-azure-bot-service/2-get-started-q na-bot",
        "references": ""
    },
    {
        "question": ": To make the knowledge base available to a bot, you must publish it as a service that can be accessed o ver _________.",
        "options": [
            "A. FTP",
            "B. SFTP",
            "C. HTTP",
            "D. HTTPS"
        ],
        "correct": "C. HTTP",
        "explanation": "Explanation To make the knowledge base available to  a bot, you must publish it as a service that can b e accessed over HTTP. Reference Link: https://docs.microsoft.com/en -in/learn/modules/build-faq-chatbot-qna-maker-azure -bot- service/3- create-bot",
        "references": ""
    },
    {
        "question": ": When your bot is ready to be delivered to users, yo u can connect it to multiple channels; making it po ssible for users to interact with it through web chat, email, Micros oft Teams, and other common communication media.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "",
        "explanation": "Explanation When your bot is ready to be delivered to users, you can connect it to multiple channels; making it possible for users to interact with it through web chat, email, Microsoft Teams, and other common communication med ia. Reference Link: https://docs.microsoft.com/en-in/learn/module s/build-faq-chatbot-qna-maker-azure-bot-service/2-g et- started-qna-bot",
        "references": ""
    },
    {
        "question": ": The Read API returns a hierarchy of information inc luding",
        "options": [
            "A. Pages",
            "B. Lines",
            "C. Regions",
            "D. Words"
        ],
        "correct": "A. Pages",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You wish to develop an application which can read s treet signs. Which azure service do you deploy?",
        "options": [
            "A. Azure Computer Vision",
            "B. Conversional Al",
            "C. Azure Custom Vision",
            "D. Machine Learning"
        ],
        "correct": "C. Azure Custom Vision",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Which Azure services are used for LUIS?",
        "options": [
            "A. Cognitive service",
            "B. Speech",
            "C. Custom Al",
            "D. Language Understanding"
        ],
        "correct": "D. Language Understanding",
        "explanation": "Explanation Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The information that we need to use to access Compu ter Vision service-",
        "options": [
            "A. IP address of host",
            "B. Key",
            "C. Endpoint",
            "D. URL"
        ],
        "correct": "B. Key",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Azure ML studio uses which type of datastores?",
        "options": [
            "A. Table",
            "B. File",
            "C. Blob",
            "D. Queue"
        ],
        "correct": "C. Blob",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": We are designing an Al solution to monitor meetings  and want to know when facial expressions indicate people being angry or scared. Which cognitive service should we use?",
        "options": [
            "A. QnA Maker",
            "B. Text Analytics",
            "C. Speech-to-text",
            "D. Face API"
        ],
        "correct": "D. Face API",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ":The Root Mean Squared Error (RMSE) is based on the same units as the label.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You wish to translate a text in French into an audi ble from in English. Which Azure service can you us e?",
        "options": [
            "A. Speech recognition",
            "B. Translator Text",
            "C. Language Understanding",
            "D. Cognitive service"
        ],
        "correct": "B. Translator Text",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": is often the foundation for any AI system by which it is trained to make predictions.",
        "options": [
            "A. ML",
            "B. AI",
            "C. Analyst",
            "D. Azure"
        ],
        "correct": "A. ML",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You wish to monitor your business's revenue to be a lerted of sudden drops In revenue. Which Azure serv ice would you deploy?",
        "options": [
            "A. Azure Custom Vision",
            "B. Azure Machine Learning designer",
            "C. Azure Anomaly detector",
            "D. Azure Computer Vision Correct Answer: C"
        ],
        "correct": "",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You are building a machine learning model to determ ine a local cab price at a specific time of a day u sing historical data from a cab service database. This is an exampl e of-",
        "options": [
            "A. Linear",
            "B. Regression",
            "C. Supervised",
            "D. UnSupervised"
        ],
        "correct": "B. Regression",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": To generate thumbnails, Computer vision can only ch ange the aspect ratio to fit the target thumbnail dimensions.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": What is the maximum file size for the Read API?",
        "options": [
            "A. 2OMB",
            "B. 5OMB",
            "C. 30MB",
            "D. 2GB",
            "A. Use the Computer Vision service - Face cannot per form facial recognition",
            "B. Use Face to retrieve age and emotional state for each person",
            "C. Use Face to create a group containing multiple im ages of each named individual, and train a",
            "D. None of the above"
        ],
        "correct": "B. Use Face to retrieve age and emotional state for each person",
        "explanation": "Explanation Creating a group that contains multiple  images of named individuals enables you to train a  facial recognition model. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/detect-analyze-faces/2-face-anal ysis- azure/",
        "references": ""
    },
    {
        "question": ": You want to extract text from images and then use t he Text Analytics service to analyze the text. You want developers to require only one key and endpoint to access all of your services. What kind of resource should you create in your Azure subscription?",
        "options": [
            "A. Computer Vision",
            "B. Cognitive Services",
            "C. Text Analytics",
            "D. All of the above"
        ],
        "correct": "B. Cognitive Services",
        "explanation": "Explanation A Cognitive Services resource support b oth Computer Vision for text extraction, and Text A nalytics for text analysis. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/read-text-computer-vision/2-o cr- azure/",
        "references": ""
    },
    {
        "question": ": You plan to use the Computer Vision service to read  text in a large PDF document. Which API should you  use?",
        "options": [
            "A. The Read API",
            "B. The OCR API",
            "C. The Recognize Text API",
            "D. None of the above"
        ],
        "correct": "A. The Read API",
        "explanation": "Explanation Not only is the Read API better suited for larger images but it runs asynchronously so it will not block your application while it is running. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/read-t ext- computer- vision/2-ocr-azure/",
        "references": ""
    },
    {
        "question": ": The Computer Vision service can not moderate the co ntent.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation The Computer Vision service can moderat e the content, detecting images that contain adult content or depict violent, gory scenes. Reference Link: https://docs. microsoft.com/en-us/learn/modules/analyze-images- computer-vision/2- image-analysis-azure",
        "references": ""
    },
    {
        "question": ": You plan to use the Form Recognizer pre-built recei pt model. Which kind of Azure resource should you c reate?",
        "options": [
            "A. Computer Vision resource.",
            "B. Form Recognizer or Cognitive Services resource",
            "C. Only Form Recognizer resource",
            "D. All of the above"
        ],
        "correct": "B. Form Recognizer or Cognitive Services resource",
        "explanation": "Explanation Both the Form Recognizer resource and C ognitive Services resource provide access to the Fo rm Recognizer service. Reference Link: https://docs.microsoft.com /en-us/learn/modules/analyze-receipts-form-recogniz er/2- receipts-azure/",
        "references": ""
    },
    {
        "question": ": You are using the Form Recognizer service to analyz e receipts that you have scanned into JPG format im ages. What is the maximum file size of JPG file you can submit  to the pre-built receipt model?",
        "options": [
            "A. 2 MB",
            "B. 200 MB",
            "C. 50 MB D. None of the above"
        ],
        "correct": "C. 50 MB D. None of the above",
        "explanation": "Explanation The maximum file size for the pre-built  receipt model is 50 MB. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/analyze-receipts-form-recognizer/2 -receipts-azure/",
        "references": ""
    },
    {
        "question": ": Speech patterns are analyzed in the audio to determ ine recognizable patterns that are mapped to words.  To accomplish this feat, the software typically uses m ultiple types of models, such as below. Choose the correct options.",
        "options": [
            "A. An acoustic model",
            "B. A Speech model",
            "C. A language model",
            "D. An object model"
        ],
        "correct": "",
        "explanation": "Explanation Speech patterns are analyzed in the aud io to determine recognizable patterns that are mapp ed to words. To accomplish this feat, the software typically uses m ultiple types of models, including: An acoustic mod el that converts the audio signal into phonemes (representations of spec ific sounds). A language model that maps phonemes t o words, usually using a statistical algorithm that predicts the mos t probable sequence of words based on the phonemes. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
        "references": ""
    },
    {
        "question": ": You are developing an application that must take En glish input from a microphone and generate a real-t ime text- based transcription in Hindi. Which service should you use?",
        "options": [
            "A. Translator Text",
            "B. Speech",
            "C. Text Analytics",
            "D. None of the above"
        ],
        "correct": "B. Speech",
        "explanation": "Explanation The Speech service can translate from a udio sources to text. Reference Link: https:// docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
        "references": ""
    },
    {
        "question": ": The model that is used by the text -to-speech API, is based on the Universal Language Model that was t rained by Microsoft.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation The model that is used by the speech-to -text API, is based on the Universal Language Model  that was trained by Microsoft. Reference Link: https://docs.microsof t.com/en-in/learn/modules/recognize-synthesize-spee ch/2- get-started- azure",
        "references": ""
    },
    {
        "question": ": You need to use the Translator Text service to tran slate email messages from Spanish into both English  and French. What is the most efficient way to accomplish this g oal?",
        "options": [
            "A. Make a single call to the service; specifying a \" from\" language of \"es\", a \"to\" language of \"en\",",
            "B. Make a single call to the service; specifying a \" from\" language of \"es\", and a \"to\" language of",
            "C. Make two calls to the service; one with a \"from\" language of \"es\" and a \"to\" language of \"en\",",
            "D. All of the above"
        ],
        "correct": "A. Make a single call to the service; specifying a \" from\" language of \"es\", a \"to\" language of \"en\",",
        "explanation": "Explanation You can specify a single \"from\" languag e and multiple \"to\" languages. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/1-introduction/",
        "references": ""
    },
    {
        "question": ": Real-time speech-to-text allows you to transcribe t ext in _______.",
        "options": [
            "A. Visual streams",
            "B. Text streams",
            "C. Audio streams",
            "D. None of the above Correct Answer: C"
        ],
        "correct": "",
        "explanation": "Explanation Real-time speech-to-text allows you to transcribe text in audio streams. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": The recognized words in Speech recognition are typi cally converted to text, which can be used for vari ous purposes. Choose the correct option.",
        "options": [
            "A. Providing closed captions for recorded or live vi deos",
            "B. Creating a transcript of a phone call or meeting",
            "C. Automated note dictation",
            "D. None of the above"
        ],
        "correct": "",
        "explanation": "Explanation The recognized words are typically conv erted to text, which you can use for various purpos es, such as. Providing closed captions for recorded or live vide os Creating a transcript of a phone call or meeting  Automated note dictation Determining intended user input for furth er processing Reference Link: https://docs.microsof t.com/en- in/learn/modules/recognize-synthesize-speech/1-intr oduction/",
        "references": ""
    },
    {
        "question": ": You need to provision an Azure resource that will b e used to author a new Language Understanding application. What kind of resource should you create?",
        "options": [
            "A. Text Analytics",
            "B. Language Understanding",
            "C. Cognitive Services",
            "D. All of the above"
        ],
        "correct": "B. Language Understanding",
        "explanation": "Explanation To author a Language Understanding mode l, you need a Language Understanding resource. Reference Link: https://docs.microsoft.com/en-in/learn/modules/crea te-language-model-with-language-understanding/1- introduction/",
        "references": ""
    },
    {
        "question": ":You have published your Language Understanding appl ication. What information does a client application developer need to get predictions from it?",
        "options": [
            "A. The endpoint and key for the application's predic tion resource",
            "B. The endpoint and key for the application's author ing resource",
            "C. The Azure credentials of the user who published t he Language Understanding application",
            "D. None of the above"
        ],
        "correct": "A. The endpoint and key for the application's predic tion resource",
        "explanation": "Explanation Client applications must connect to the  endpoint of the prediction resource, specifying an associated authentication key. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/create-language-mod el- with-language- understanding/1-introduction/",
        "references": ""
    },
    {
        "question": ": It should be run in an asynchronous manner because the batch jobs are scheduled on a best-effort basis . Choose the correct option.",
        "options": [
            "A. Business Transcription",
            "B. Real-time transcription",
            "C. Phonetic transcription",
            "D. Batch transcription"
        ],
        "correct": "D. Batch transcription",
        "explanation": "Explanation Batch transcription should be run in an  asynchronous manner because the batch jobs are scheduled on a best- effort basis. Normally a job will start executing w ithin minutes of the request but there is no estima te for when a job changes into the running state. Reference Link: https://doc s.microsoft.com/en-in/learn/modules/recognize-synth esize- speech/2-get- started-azure",
        "references": ""
    },
    {
        "question": ": A speech synthesis solution typically requires the following information. Choose the correct option.",
        "options": [
            "A. The text to be spoken",
            "B. The speech to be spoken",
            "C. The voice to be used to vocalize the speech",
            "D. All of the above"
        ],
        "correct": "",
        "explanation": "Explanation A speech synthesis solution typically r equires the following information: The text to be s poken. The voice to be used to vocalize the speech. Reference Link: https: //docs.microsoft.com/en-in/learn/modules/recognize- synthesize-speech/1- introduction/",
        "references": ""
    },
    {
        "question": ": You are authoring a Language Understanding applicat ion to support an international clock. You want use rs to be able to ask for the current time in a specified cit y, for example \"What is the time in London?\". What should you do?",
        "options": [
            "A. Define a \"city\" entity and a \"GetTime\" intent wit h utterances that indicate the city intent.",
            "B. Create an intent for each city, each with an utte rance that asks for the time in that city.",
            "C. Add the utterance \"What time is it in city\" to th e \"None\" intent.",
            "D. None of the above"
        ],
        "correct": "A. Define a \"city\" entity and a \"GetTime\" intent wit h utterances that indicate the city intent.",
        "explanation": "Explanation The intent encapsulates the task (getti ng the time) and the entity specifies the item to w hich the intent is applied (the city). Reference Link: https://docs.microsoft. com/en-in/learn/modules/create-language-model-with- language- understanding/1-introduction/",
        "references": ""
    },
    {
        "question": ": For customer support scenarios, it's common to crea te a bot that can interpret and answer frequently a sked questions through a website chat window, email, or voice interface.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation For customer support scenarios, it's co mmon to create a bot that can interpret and answer frequently asked questions through a website chat window, email, or voice interface. Reference Link: https://docs.micro soft.com/ en- in/learn/modules/build-faq-chatbot-qna-maker-azure- bot-service/3-create-bot",
        "references": ""
    },
    {
        "question": ": You can use the ________ to create and host a bot t hat uses the knowledge base to answer user question s. A. Azure LUIS Service",
        "options": [
            "B. Azure QnA Maker Service",
            "C. Azure Bot Service",
            "D. None of the above"
        ],
        "correct": "C. Azure Bot Service",
        "explanation": "Explanation You can then use the Azure Bot Service to create and host a bot that uses the knowledge ba se to answer user questions. Reference Link: https://docs.microsoft.c om/en-in/learn/modules/build-faq-chatbot-qna-maker- azure- bot- service/3-create-bot",
        "references": ""
    },
    {
        "question": ": Your knowledge base is based on the details in the _______ and some __________.",
        "options": [
            "A. QnA Maker",
            "B. pre-defined responses",
            "C. Database",
            "D. FAQ document"
        ],
        "correct": "",
        "explanation": "Explanation Your knowledge base is based on the det ails in the FAQ document and some pre-defined responses. Reference Link: https://docs.microsoft.com/en-in/learn/module s/build-faq-chatbot-qna-maker-azure-bot-service/3-c reate- bot",
        "references": ""
    },
    {
        "question": ": Once you create your bot, you can manage it in the Azure portal, where you can do the following. Choos e the correct options.",
        "options": [
            "A. Extend the bot's functionality by adding custom c ode",
            "B. Test the bot in an interactive test interface.",
            "C. Configure logging, analytics, and integration wit h other services.",
            "D. All of the above"
        ],
        "correct": "D. All of the above",
        "explanation": "Explanation After creating your bot, you can manage  it in the Azure portal, where you can: Extend the bot's functionality by adding custom code. Test the bot in an interactive test interface. Configure logging, analytics, and i ntegration with other services. Reference Link: https://docs.microsoft.co m/en-in/learn/modules/build-faq-chatbot-qna-maker-a zure- bot-service/2- get-started-qna-bot",
        "references": ""
    },
    {
        "question": ": You can always use the QnA Maker portal to edit the  knowledge base to improve it, and republish it.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation You can always use the QnA Maker portal  to edit the knowledge base to improve it, and repu blish it. Reference Link: https://docs.microsoft.com/en-in/learn/module s/build-faq-chatbot-qna-maker-azure-bot-service/3-c reate- bot",
        "references": ""
    },
    {
        "question": ": The _______ shows the full text in the FAQ document  for the closest matched question, while the ______  is intelligently extracted from the passage.",
        "options": [
            "A. answer passage",
            "B. long answer",
            "C. short answer",
            "D. question passage"
        ],
        "correct": "",
        "explanation": "Explanation The answer passage shows the full text in the FAQ document for the closest matched questio n, while the short answer is intelligently extrhttps://docs.microsoft. com/en-in/learn/modulacted from the passage. Refere nce Link: es/build- faq-chatbot-qna-maker-azure-bot-service/3-create-bo t",
        "references": ""
    },
    {
        "question": ": Predicting age of a person is an example of _______ __________.",
        "options": [
            "A. regression",
            "B. classification",
            "C. clustering",
            "D. All of the above"
        ],
        "correct": "",
        "explanation": "Explanation Predicting age of a person is an exampl e of regression.",
        "references": ""
    },
    {
        "question": ": Below principles fall under the category of respons ible AI? Choose the correct options.",
        "options": [
            "A. Fairness",
            "B. Reliability and safety",
            "C. Excludeness",
            "D. Inclusiveness"
        ],
        "correct": "",
        "explanation": "Explanation Fairness, Reliability and safety, Inclu siveness are the part of principles fall under the category of responsible AI. Reference Link: https://docs.microsoft.com/en-u s/learn/modules/get-started-ai-fundamentals/8-under stand- responsible-ai",
        "references": ""
    },
    {
        "question": ": An innocent person is convicted of a crime based on  evidence from facial recognition. Under which AI challenge the following example is categorized.",
        "options": [
            "A. Solutions may not work for everyone",
            "B. Who's liable for AI-driven decisions?",
            "C. Users must trust a complex system",
            "D. Errors may cause harm"
        ],
        "correct": "B. Who's liable for AI-driven decisions?",
        "explanation": "Explanation Who's liable for AI-driven decisions? -  An innocent person is convicted of a crime based o n evidence from facial recognition ? who's responsible? Reference L ink: https://docs.microsoft.com/en-us/learn/modules /get- started-ai- fundamentals/7-challenges-with-ai",
        "references": ""
    },
    {
        "question": ": People should be accountable for AI systems. Which principle defines this requirement?",
        "options": [
            "A. Transparency",
            "B. Accountability C. Inclusiveness",
            "D. Fairness"
        ],
        "correct": "B. Accountability C. Inclusiveness",
        "explanation": "Explanation Accountability: People should be accoun table for AI systems. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/get-started-ai-fundamentals/8-unde rstand-responsible-ai",
        "references": ""
    },
    {
        "question": ": A loan-approval model discriminates by gender due t o bias in the data with which it was trained. Under  which AI challenge the following example is categorized.",
        "options": [
            "A. Data could be exposed",
            "B. Bias can affect results",
            "C. Errors may cause harm",
            "D. Users must trust a complex system"
        ],
        "correct": "B. Bias can affect results",
        "explanation": "Explanation Bias can affect results - A loan-approv al model discriminates by gender due to bias in the  data with which it was trained Reference Link: https://docs.microsoft. com/en-us/learn/modules/get-started-ai-fundamentals /7- challenges-with- ai",
        "references": ""
    },
    {
        "question": ": AI systems should be understandable. Which principl e defines this requirement?",
        "options": [
            "A. Transparency",
            "B. Accountability",
            "C. Inclusiveness",
            "D. Fairness"
        ],
        "correct": "A. Transparency",
        "explanation": "Explanation Transparency: AI systems should be unde rstandable. Users should be made fully aware of the purpose of the system, how it works, and what limitations may be e xpected. Reference Link: https://docs.microsoft.com /en- us/learn/modules/get-started-ai-fundamentals/8-unde rstand-responsible-ai",
        "references": ""
    },
    {
        "question": ":At Microsoft, AI software development is guided by a set of _______ principles.",
        "options": [
            "A. seven",
            "B. Bsix",
            "C. five",
            "D. Four"
        ],
        "correct": "B. Bsix",
        "explanation": "Explanation At Microsoft, AI software development i s guided by a set of six principles. Reference Link : https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/8-understand-responsible-ai",
        "references": ""
    },
    {
        "question": ": AI systems should empower everyone and engage peopl e. Which principle defines this requirement?",
        "options": [
            "A. Transparency",
            "B. Accountability",
            "C. Inclusiveness",
            "D. Fairness"
        ],
        "correct": "C. Inclusiveness",
        "explanation": "Explanation Inclusiveness: AI systems should empowe r everyone and engage people. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/8-understand-responsible-ai",
        "references": ""
    },
    {
        "question": ": Designers and developers of AI-based solution shoul d work within a framework of _______ and __________ that ensure the solution meets ethical and legal standar ds that are clearly defined.",
        "options": [
            "A. governance",
            "B. organizational principles",
            "C. protocols",
            "D. Law"
        ],
        "correct": "",
        "explanation": "Explanation In Accountability, Designers and develo pers of AI-based solution should work within a fram ework of governance and organizational principles that ensur e the solution meets ethical and legal standards th at are clearly defined. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/8-understan d- responsible-ai",
        "references": ""
    },
    {
        "question": ": AI systems should perform unreliably and safely.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation AI systems should perform reliably and safely. Unreliability in these kinds of system can result in substantial risk to human life. Reference Link: https://docs.mi crosoft.com/en-us/learn/modules/get-started-ai- fundamentals/8- understand-responsible-ai",
        "references": ""
    },
    {
        "question": ": What is the function of Average Distance to Other C enter metric in clustering?",
        "options": [
            "A. This indicates how close, on average, each point in the cluster is to the centroids of all other",
            "B. This indicates how close, on average, each point in the cluster is to the centroid of the cluster.",
            "C. The number of points assigned to the cluster.",
            "D. None of the above"
        ],
        "correct": "A. This indicates how close, on average, each point in the cluster is to the centroids of all other",
        "explanation": "Explanation Average Distance to Other Center: This indicates how close, on average, each point in the cluster is to the centroids of all other clusters. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/create - clustering-model- azure-machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": You are using an Azure Machine Learning designer pi peline to train and test a K-Means clustering model . You want your model to assign items to one of three clusters . Which configuration property of the K-Means Clust ering module should you set to accomplish this?",
        "options": [
            "A. Set Number of Centroids to 3",
            "B. Set Random number seed to 3",
            "C. Set Iterations to 3",
            "D. All of the above"
        ],
        "correct": "",
        "explanation": "Explanation To create K clusters, you must set the number of centroids to K. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/deploy-service",
        "references": ""
    },
    {
        "question": ": In clustering, this metric indicates how close, on average, each point in the cluster is to the centro id of the cluster. Choose the correct option.",
        "options": [
            "A. Average Distance to Other Center",
            "B. Average Distance to Cluster Center",
            "C. Number of Edges",
            "D. Number of Points"
        ],
        "correct": "B. Average Distance to Cluster Center",
        "explanation": "Explanation Average Distance to Cluster Center: Thi s indicates how close, on average, each point in th e cluster is to the centroid of the cluster.",
        "references": ""
    },
    {
        "question": ": You can think of machine learning as a way of defin ing a function (let's call it f) that operates on o ne or more features of something (which we'll call x) to calcu late a predicted label (y).",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Mathematically, you can think of machin e learning as a way of defining a function (let's c all it f) that operates on one or more features of something (which we'll c all x) to calculate a predicted label (y) - like th is: f(x) = y Reference Link: https://docs.microsoft.com/en-us/learn/module s/use-automated-machine-learning/what-is-ml",
        "references": ""
    },
    {
        "question": ": Once you create and run a pipeline to train the clu stering model, you can create an _________ that use s the model to assign new data observations to clusters.",
        "options": [
            "A. Deployment pipeline B. Performance pipeline",
            "C. Inference pipeline",
            "D. All of the above"
        ],
        "correct": "C. Inference pipeline",
        "explanation": "Explanation After creating and running a pipeline t o train the clustering model, you can create an inf erence pipeline that uses the model to assign new data observations to cluste rs. Reference Link: https://docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/inference-pipeline",
        "references": ""
    },
    {
        "question": ": You use Azure Machine Learning designer to create a  training pipeline for a clustering model. Now you want to use the model in an inference pipeline. Which module sh ould you use to infer cluster predictions from the model?",
        "options": [
            "A. Score Model",
            "B. Assign Data to Clusters",
            "C. Train Clustering Model",
            "D. None of the above"
        ],
        "correct": "B. Assign Data to Clusters",
        "explanation": "Explanation Use the Assign Data to Clusters module to generate cluster predictions from a trained clus tering model. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-clustering-model-azure-machine- learning- designer/deploy-service",
        "references": ""
    },
    {
        "question": ": The maximum of the distances between each point and  the centroid of that point?s cluster. Choose the c orrect matrix of clustering.",
        "options": [
            "A. Maximal Distance to Cluster Center",
            "B. Average Distance to Cluster Center",
            "C. Number of Edges",
            "D. Number of Points"
        ],
        "correct": "A. Maximal Distance to Cluster Center",
        "explanation": "Explanation Maximal Distance to Cluster Center: The  maximum of the distances between each point and th e centroid of that point?s cluster. Reference Link: https://docs.micro soft.com/en-us/learn/modules/create-clustering-mode l-azure- machine- learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": Explain best model option in Automated ML can calcu late feature importance for the best model.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Explain best model: Selected - this opt ion causes automated machine learning to calculate feature importance for the best model; making it possible to determine  the influence of each feature on the predicted lab el. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
        "references": ""
    },
    {
        "question": ": Operations that you run are called ___________ in A zure Machine Learning.",
        "options": [
            "A. Programs",
            "B. Scripts",
            "C. Experiments",
            "D. Notebooks"
        ],
        "correct": "C. Experiments",
        "explanation": "Explanation Operations that you run are called expe riments in Azure Machine Learning. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
        "references": ""
    },
    {
        "question": ": In clustering, this metric indicates the number of points assigned to the cluster. Choose the correct option.",
        "options": [
            "A. Points count",
            "B. Average points",
            "C. Number of Edges",
            "D. Number of Points"
        ],
        "correct": "D. Number of Points",
        "explanation": "Explanation Explanation Number of Points: The number of points assigned to the cluster. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-clustering-model-azure-mach ine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": Azure Machine Learning studio provides a more focus ed user interface for managing workspace resources to data scientists and Machine Learning operations engineer s.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation You can manage your workspace using the  Azure portal, but for data scientists and Machine Learning operations engineers, Azure Machine Learning studio  provides a more focused user interface for managin g workspace resources. Reference Link: https://docs.microsoft.c om/en-us/learn/modules/use-automated-machine-learni ng/ what-is-ml",
        "references": ""
    },
    {
        "question": ": It uses mathematics and statistics to create a mode l that can predict unknown values. Choose the corre ct option.",
        "options": [
            "A. Machine Learning",
            "B. Deep Learning",
            "C. Natural Language Processing",
            "D. Computer Vision"
        ],
        "correct": "A. Machine Learning",
        "explanation": "Explanation Machine learning is a technique that us es mathematics and statistics to create a model tha t can predict unknown values. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/use-automated-machine-learning/ what-is-ml",
        "references": ""
    },
    {
        "question": ": This statistic in combination with the Average Dist ance to Cluster Center helps you determine the clus ters spread ?",
        "options": [
            "A. Maximal Distance to Cluster Center",
            "B. Average Distance to Cluster Center",
            "C. Number of Edges",
            "D. Number of Points Correct Answer: A"
        ],
        "correct": "",
        "explanation": "Explanation Maximal Distance to Cluster Center stat istic in combination with the Average Distance to C luster Center helps you determine the cluster?s spread. Reference Link:  https://docs.microsoft.com/en-us/learn/modules/cre ate- clustering- model-azure-machine-learning-designer/evaluate-mode l",
        "references": ""
    },
    {
        "question": ": Information is required to connect to your deployed  service from a client application are REST endpoin t and __________. Choose the correct option.",
        "options": [
            "A. Primary Key for your service",
            "B. Password for your service.",
            "C. Token for your service.",
            "D. All of the above"
        ],
        "correct": "A. Primary Key for your service",
        "explanation": "Explanation You need below information to connect t o your deployed service from a client application. The REST endpoint for your service the Primary Key for your service R eference Link: https://docs.microsoft.com/en-us/lea rn/ modules/use- automated-machine-learning/deploy-model",
        "references": ""
    },
    {
        "question": ": The specific operation that the f function performs  on x to calculate y depends on a number of factors , including the type of model you're trying to create and the speci fic algorithm used to train the model.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation The specific operation that the f funct ion performs on x to calculate y depends on a numbe r of factors, including the type of model you're trying to create and the s pecific algorithm used to train the model. Addition ally in most cases, the data used to train the machine learning model requi res some pre-processing before model training can b e performed. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/use-automated-machine-learning/what-is- ml",
        "references": ""
    },
    {
        "question": "What is the function of Average Distance to Cluster  Center metric in clustering?",
        "options": [
            "A. The maximum of the distances between each point a nd the centroid of that point?s cluster.",
            "B. This indicates how close, on average, each point in the cluster is to the centroid of the cluster.",
            "C. This indicates how close, on average, each point in the cluster is to the centroids of all other",
            "D. All of the above"
        ],
        "correct": "B. This indicates how close, on average, each point in the cluster is to the centroid of the cluster.",
        "explanation": "Explanation Average Distance to Cluster Center: Thi s indicates how close, on average, each point in th e cluster is to the centroid of the cluster. Reference Link: https://do cs.microsoft.com/en-us/learn/modules/create-cluster ing- model-azure- machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": You plan to use Face to detect human faces in an im age. How does the service indicate the location of the faces it detects?",
        "options": [
            "A. A pair of coordinates for each face, indicating t he center of the face",
            "B. Two pairs of coordinates for each face, indicatin g the location of the eyes",
            "C. A set of coordinates for each face, defining a re ctangular bounding box around the face",
            "D. None of the above"
        ],
        "correct": "C. A set of coordinates for each face, defining a re ctangular bounding box around the face",
        "explanation": "Explanation The location of detected faces are indi cated by a coordinates for a rectangular bounding b ox. Reference Link: https://docs.microsoft.com/en-us/learn/modules/dete ct-analyze-faces/2-face-analysis-azure/",
        "references": ""
    },
    {
        "question": ": What is one aspect that may impair facial detection ?",
        "options": [
            "A. Smile expression",
            "B. Extreme angles",
            "C. Fast shutter speed",
            "D. All of the above"
        ],
        "correct": "B. Extreme angles",
        "explanation": "Explanation Best results are obtained when the face s are full-frontal or as near as possible to full-f rontal Reference Link: https://docs.microsoft.com/en-us/learn/modules/dete ct-analyze-faces/2-face-analysis-azure/",
        "references": ""
    },
    {
        "question": ": You can use the Custom Vision cognitive service to train image classification models and deploy them a s services for applications to use.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation You can use the Custom Vision cognitive  service to train image classification models and d eploy them as services for applications to use. Reference Link: h ttps://docs.microsoft.com/en-us/learn/modules/class ify- images-custom- vision/1a-overview-classification",
        "references": ""
    },
    {
        "question": ": Which workload is used for evaluating images from X -ray or MRI devices could quickly classify specific  issues found as cancerous tumors, or many other medical conditio ns related to medical imaging diagnosis?",
        "options": [
            "A. Image analysis",
            "B. Image processing",
            "C. Image classification",
            "D. Image manipulation"
        ],
        "correct": "C. Image classification",
        "explanation": "Explanation Medical diagnosis: evaluating images fr om X-ray or MRI devices could quickly classify spec ific issues found as cancerous tumors, or many other medical conditio ns related to medical imaging diagnosis. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/1-introduction",
        "references": ""
    },
    {
        "question": ": Which programming languages are supported in Azure machine learning Designer?",
        "options": [
            "A. C#",
            "B. Python",
            "C. C++",
            "D. C Programming Correct Answer: B"
        ],
        "correct": "",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You wish to develop an application which can take v erbal commands. What Azure service should you provision?",
        "options": [
            "A. Translator Text",
            "B. Analysis",
            "C. Speech",
            "D. Computer Vision"
        ],
        "correct": "C. Speech",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The Text-to-Speech Neural voices leverage Neural ne tworks resulting in a more robotic-sounding voice.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You have used the wrong language code in Text Analy tics. What sentiment analysis score should you expe ct?",
        "options": [
            "A. 0",
            "B. 1",
            "C. 3",
            "D. 2"
        ],
        "correct": "A. 0",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ":The OCR API in Azure Computer Vision service Is use d to scan newspapers and magazines.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Computer vision is the best Azure resource for dete cting, analyzing and working with Faces.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": What is the easiest method to define elements of yo ur LUIS model?",
        "options": [
            "A. ml.azure.ai",
            "B. Cognitive service portal",
            "C. LUIS portal",
            "D. Writing code"
        ],
        "correct": "C. LUIS portal",
        "explanation": "Explanation Language Understanding (LUIS) A machine  learning-based service to build natural language i nto apps, bots, and IoT devices. Quickly create enterprise-ready, c ustom models that continuously improve.",
        "references": ""
    },
    {
        "question": ": Which module should you use to provide a simple met ric to compare the performance of multiple training models?",
        "options": [
            "A. Evaluate Model",
            "B. Score Model",
            "C. Compare Model",
            "D. Linear regression"
        ],
        "correct": "",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Deploying an Al service that monitors people of cer tain ethnicity for closer inspection in a retail st ore Is a violation of Microsoft responsible Al principle?",
        "options": [
            "A. Accountability",
            "B. Fairness",
            "C. Transparency",
            "D. Inclusiveness"
        ],
        "correct": "D. Inclusiveness",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You use the Text Analytics service to perform senti ment analysis on a document, and a score of 0.99 Is returned. What does this score indicate about the document se ntiment?",
        "options": [
            "A. The document is neutral.",
            "B. The document Is negative.",
            "C. The document is positive.",
            "D. None"
        ],
        "correct": "C. The document is positive.",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": If you consider the concept of `Describing an Image ' of Computer Vision, which of the following are co rrect:",
        "options": [
            "A. Based on the image content, Computer Vision may r eturn multiple phrases",
            "B. Each returned phrase will be associated with a co nfidence score",
            "C. The phrases will be arranged in ascending order o f their confidence score",
            "D. The phrases will be arranged in descending order of their confidence score",
            "A.",
            "B.",
            "C.",
            "D."
        ],
        "correct": "D. The phrases will be arranged in descending order of their confidence score",
        "explanation": "Explanation Project ID: The unique ID of the Custom  Vision project you created to train the model. Ref erence Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
        "references": ""
    },
    {
        "question": ": The performance for the trained model is indicated by the following evaluation metrics in custom visio n service. Choose the correct option.",
        "options": [
            "A. Precision",
            "B. Recall",
            "C. Mean Absolute Error(MAE)",
            "D. Average Precision (AP)"
        ],
        "correct": "",
        "explanation": "Explanation Explanation At the end of the training process in c ustom vision, the performance for the trained model  is indicated by the following evaluation metrics: Precision, Recall, Av erage Precision (AP). Reference Link: https:// docs.microsoft.com/en- us/learn/modules/classify-images-custom-vision/2-az ure-image-classification",
        "references": ""
    },
    {
        "question": ": You plan to use the Custom Vision service to train an image classification model. You want to create a  resource that can only be used for model training, and not for pr ediction. Which kind of resource should you create in your Azure subscription?",
        "options": [
            "A. Custom Vision",
            "B. Cognitive Services",
            "C. Computer Vision",
            "D. None of the above"
        ],
        "correct": "A. Custom Vision",
        "explanation": "Explanation When you create a Custom Vision resourc e, you can specify whether it is to be used for tra ining, prediction, or both. Reference Link: https://docs.microsoft.com/en -us/learn/modules/classify-images-custom-vision/2-a zure- image- classification",
        "references": ""
    },
    {
        "question": ": The Computer Vision service can detect image color schemes.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation The Computer Vision service can detect image color schemes, specifically, identifying the dominant foreground, background, and overall colors in an im age. Reference Link: https://docs.microsoft.com/en- us/learn/modules/analyze-images-computer-vision/2-i mage-analysis-azure",
        "references": ""
    },
    {
        "question": ": Given example, the following restaurant review coul d be analyzed for sentiment. \"Our dining experience  at this restaurant was one of the worst I've ever had. The service was slow, and the food was awful. I'll neve r eat at this establishment again.\"",
        "options": [
            "A. 0.5 B. 1",
            "C. 0.1",
            "D. 0.9"
        ],
        "correct": "C. 0.1",
        "explanation": "Explanation The score for the review might be close r to 0.1, indicating a negative sentiment. Referenc e Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": You can use the _________ capabilities of the Langu age service to summarize the main points for sentim ent analysis.",
        "options": [
            "A. Sentiment analysis",
            "B. Language Understanding Intelligent Service (LUIS)",
            "C. Text analytics",
            "D. Key phrase extraction"
        ],
        "correct": "D. Key phrase extraction",
        "explanation": "Explanation You can use the key phrase extraction c apabilities of the Language service to summarize th e main points for sentiment analysis. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/analyze-text-with-t ext- analytics- service/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": Sentiment scores that are close to the middle of th e range (0.5) are considered ___________ or ______________.",
        "options": [
            "A. Neutral",
            "B. Negative",
            "C. Positive",
            "D. Indeterminate"
        ],
        "correct": "",
        "explanation": "Explanation Sentiment scores that are close to the middle of the range (0.5) are considered neutral or indeterminate.",
        "references": ""
    },
    {
        "question": ":Using the language service to analyze the text \":-) \", results in a value of unknown for the language n ame and the language identifier, and a score of NaN.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Using the service to analyze the text \" :-)\", results in a value of unknown for the languag e name and the language identifier, and a score of NaN. Reference Link: https://docs.microsoft.com/en-in/learn/module s/ analyze-text-with- text-analytics-service/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": A sentiment score may be _______ is in the case whe re the wrong language code was used.",
        "options": [
            "A. 1",
            "B. 0.5",
            "C. 0",
            "D. 0.9"
        ],
        "correct": "B. 0.5",
        "explanation": "Explanation A score may be 0.5 is in the case where  the wrong language code was used. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": You can provide the Language service with unstructu red text and it will return a ________ in the text that it recognizes.",
        "options": [
            "A. List of objects",
            "B. List of entities",
            "C. List of files",
            "D. List of phrases"
        ],
        "correct": "B. List of entities",
        "explanation": "Explanation You can provide the Language service wi th unstructured text and it will return a list of e ntities in the text that it recognizes. Reference Link: https://docs.microsoft. com/en-in/learn/modules/analyze-text-with-text-anal ytics- service/2-get- started-azure",
        "references": ""
    },
    {
        "question": ": The entity detection service supports _______ to he lp disambiguate entities by linking to a specific r eference.",
        "options": [
            "A. Entity linking",
            "B. Entity relationship",
            "C. Entity pairing",
            "D. Entity listing"
        ],
        "correct": "A. Entity linking",
        "explanation": "Explanation The service also supports entity linkin g to help disambiguate entities by linking to a spe cific reference. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/analyze-text-with-text-analytics-servic e/2-get- started-azure",
        "references": ""
    },
    {
        "question": ": The text analytics capabilities in the Language ser vice can do the following for each sentence. Choose  the correct option.",
        "options": [
            "A. Evaluate text",
            "B. Return objects",
            "C. Return sentiment scores",
            "D. Return labels"
        ],
        "correct": "",
        "explanation": "Explanation The text analytics capabilities in the Language service can evaluate text and return senti ment scores and labels for each sentence. Reference Link: https://docs.mic rosoft.com/en-in/learn/modules/analyze-text-with-te xt- analytics- service/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": For recognized entities, the Entity recognition ser vice returns a URL for a relevant _______ article.",
        "options": [
            "A. Google",
            "B. Twitter",
            "C. Wikipedia",
            "D. All of the above"
        ],
        "correct": "C. Wikipedia",
        "explanation": "Explanation For recognized entities, the service re turns a URL for a relevant Wikipedia article. Refer ence Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": Microsoft Azure Cognitive Services includes the tex t analytics capabilities in the Language service, w hich provides some out-of-the-box NLP capabilities, including the  identification of _________ in text, and the class ification of text based on ___________.",
        "options": [
            "A. Key phrases",
            "B. Entities",
            "C. Sentiment",
            "D. Language"
        ],
        "correct": "",
        "explanation": "Explanation Microsoft Azure Cognitive Services incl udes the text analytics capabilities in the Languag e service, which provides some out-of-the-box NLP capabilities, incl uding the identification of key phrases in text, an d the classification of text based on sentiment. Reference Link: https://do cs.microsoft.com/en-in/learn/modules/analyze-text-w ith-text- analytics- service/3-exercise",
        "references": ""
    },
    {
        "question": ": The confidence score may be less than 1 as a result  of the mixed language text.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation The confidence score may be less than 1  as a result of the mixed language text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": The Universal Language Model that was trained by Mi crosoft is optimized for two scenarios. Choose the correct options.",
        "options": [
            "A. Typing",
            "B. Conversational C. Transactional",
            "D. Dictation"
        ],
        "correct": "",
        "explanation": "Explanation The model is optimized for two scenario s, conversational and dictation. Reference Link: https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": when using a home automation system, a user might u se the following term. Choose the correct option.",
        "options": [
            "A. Entities",
            "B. Intents",
            "C. Utterances",
            "D. Objects"
        ],
        "correct": "C. Utterances",
        "explanation": "Explanation An utterance is an example of something  a user might say, and which your application must interpret. For example, when using a home automation system, a use r might use the following utterances: \"Switch the f an on.\" \"Turn on the light.\"",
        "references": ""
    },
    {
        "question": ": The _________ is a cognitive service in Azure that enables you to quickly create a knowledge base, eit her by entering question and answer pairs or from an existing docum ent or web page.",
        "options": [
            "A. QnA Maker service",
            "B. Bot service",
            "C. LUIS service",
            "D. None of the above"
        ],
        "correct": "A. QnA Maker service",
        "explanation": "Explanation The QnA Maker service is a cognitive se rvice in Azure that enables you to quickly create a knowledge base, either by entering question and answer pairs or fro m an existing document or web page. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/3-create- bot",
        "references": ""
    },
    {
        "question": ":Which option is available to create a knowledge bas e on QnA Maker portal?",
        "options": [
            "A. Initiate a knowledge base.",
            "B. Create a knowledge base",
            "C. Choose a knowledge base.",
            "D. None of the above"
        ],
        "correct": "B. Create a knowledge base",
        "explanation": "Explanation In the QnA Maker portal, select Create a knowledge base to create a knowledge base. Refere nce Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/3-create- bot",
        "references": ""
    },
    {
        "question": ": If you have already provisioned a free-tier _______ __ resources, your quota may not allow you to creat e another one.",
        "options": [
            "A. Azure Cognitive Search",
            "B. Azure search",
            "C. Azure Inference Clsuter (AIC)",
            "D. None of the above"
        ],
        "correct": "A. Azure Cognitive Search",
        "explanation": "Explanation If you have already provisioned a free- tier Azure Cognitive Search resources, your quota m ay not allow you to create another one. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/build-faq-chatbot-q na- maker-azure-bot- service/3-create-bot",
        "references": ""
    },
    {
        "question": ": A knowledge base that consists of question-and-answ er pairs as of following. Choose the correct option s.",
        "options": [
            "A. Generated from an existing FAQ document or web pa ge.",
            "B. Imported from a pre-defined chit-chat data source .",
            "C. Entered and edited manually.",
            "D. None of the above"
        ],
        "correct": "",
        "explanation": "Explanation Once you provision a QnA Maker resource , you can use the QnA Maker portal to create a knowledge base that consists of question-and-answer pairs. These questi ons and answers can be: Generated from an existing FAQ document or web page. Imported from a pre-defined chit-chat dat a source. Entered and edited manually.",
        "references": ""
    },
    {
        "question": ": Which service provides a dedicated QnA Maker portal  web-based interface that you can use to create, tr ain, publish, and manage knowledge bases?",
        "options": [
            "A. QnA Maker",
            "B. Robots service",
            "C. Bots service",
            "D. LUIS service"
        ],
        "correct": "",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Underlying the bot interface is a knowledge base of  questions and appropriate answers that the bot can  search for suitable responses.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Underlying the bot interface is a knowl edge base of questions and appropriate answers that  the bot can search for suitable responses. Reference Link: https://doc s.microsoft.com/en-in/learn/modules/build-faq-chatb ot-qna- maker-azure- bot-service/3-create-bot",
        "references": ""
    },
    {
        "question": ": Which service to train a language model that can un derstand spoken or text-based commands?",
        "options": [
            "A. Speech",
            "B. Language Understanding Intelligent Service (LUIS)",
            "C. Translator Text",
            "D. Text Analytics Correct Answer: B"
        ],
        "correct": "",
        "explanation": "Explanation Language Understanding Intelligent Serv ice (LUIS) service is used to train a language mode l that can understand spoken or text-based commands. Reference  Link: https://docs.microsoft.com/en-us/learn/modul es/ get-started-ai- fundamentals/5-understand-natural-language-process",
        "references": ""
    },
    {
        "question": ": Language Understanding Intelligent Service (LUIS) s ervice is used to train a language model for below tasks. Choose the correct option.",
        "options": [
            "A. To understand spoken commands",
            "B. To translate spoken languages",
            "C. To understand text-based commands",
            "D. To recognize and synthesize speech"
        ],
        "correct": "",
        "explanation": "Explanation Language Understanding Intelligent Serv ice (LUIS) service to train a language model that c an understand spoken or text-based commands. Reference Link: http s://docs.microsoft.com/en-us/learn/modules/get-star ted- ai- fundamentals/5-understand-natural-language-process",
        "references": ""
    },
    {
        "question": ": A relative metric between 0 and 1 based on the abso lute differences between predicted and true values.",
        "options": [
            "A. Relative Absolute Error (RAE)",
            "B. Relative Squared Error (RSE)",
            "C. Root Mean Squared Error (RMSE)",
            "D. Mean Absolute Error (MAE)",
            "A. Relative Absolute Error (RAE)",
            "B. Relative Squared Error (RSE)",
            "C. Root Mean Squared Error (RMSE)",
            "D. Mean Absolute Error (MAE)"
        ],
        "correct": "B. Relative Squared Error (RSE)",
        "explanation": "Explanation Relative Squared Error (RSE): A relativ e metric between 0 and 1 based on the square of the differences between predicted and true values. The closer to 0 this metric is, the better the model is performing.  Because this metric is relative, it can be used to compare models where th e labels are in different units. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te-regression-model-azure-machine-learning-designer / evaluate-model",
        "references": ""
    },
    {
        "question": ": This metric summarizes how much of the variance bet ween predicted and true values is explained by the model. Choose the correct option.",
        "options": [
            "A. Coefficient of Determination (R2)",
            "B. Relative Squared Error (RSE)",
            "C. Root Mean Squared Error (RMSE)",
            "D. Mean Absolute Error (MAE)"
        ],
        "correct": "A. Coefficient of Determination (R2)",
        "explanation": "Explanation Coefficient of Determination (R2): This  metric is more commonly referred to as R-Squared, and summarizes how much of the variance between predicted and true  values is explained by the model. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te-regression-model-azure-machine-learning-designer / evaluate-model",
        "references": ""
    },
    {
        "question": ": The closer to 0 this metric is, the better the mode l is performing.",
        "options": [
            "A. Relative Absolute Error (RAE)",
            "B. Relative Squared Error (RSE)",
            "C. Root Mean Squared Error (RMSE)",
            "D. Mean Absolute Error (MAE)"
        ],
        "correct": "",
        "explanation": "Explanation Relative Squared Error (RSE) & Relative  Absolute Error (RAE) : The closer to 0 this metric  is, the better the model is performing. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/create-regression- model- azure- machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": The OCR API in Azure Computer Vision service Is use d to scan newspapers and magazines",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The ability of a software agent to participate in a  conversation is known as",
        "options": [
            "A. Natural Language processioning",
            "B. Conversional Al",
            "C. Text Analysis",
            "D. Speech Recognition"
        ],
        "correct": "B. Conversional Al",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Which Azure service would you deploy to detect a su dden spike in network traffic?",
        "options": [
            "A. Azure AutoML",
            "B. Azure Conative services",
            "C. Azure Anomaly detector",
            "D. Azure machine learning",
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The area of AI that deals with creating software th at understands written and spoken language. Choose the correct option.",
        "options": [
            "A. Conversational AI",
            "B. Responsible AI",
            "C. Natural language processing (NLP)",
            "D. All of the above"
        ],
        "correct": "C. Natural language processing (NLP)",
        "explanation": "Explanation Natural language processing (NLP) is th e area of AI that deals with creating software that understands written and spoken language. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/get-started-ai- fundamentals/5- understand-natural-language-process",
        "references": ""
    },
    {
        "question": ": NLP enables you to create software that can do the following. Choose the correct options.",
        "options": [
            "A. Analyze and interpret text in documents, email me ssages, and other sources.",
            "B. Reservation systems for restaurants, airlines, ci nemas, and other appointment based businesses.",
            "C. Interpret spoken language, and synthesize speech responses.",
            "D. Interpret commands and determine appropriate acti ons."
        ],
        "correct": "",
        "explanation": "Explanation NLP enables you to create software that  can: Analyze and interpret text in documents, emai l messages, and other sources. Interpret spoken language, and synth esize speech responses. Automatically translate spo ken or written phrases between languages. Interpret commands and determine  appropriate actions. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/get-started-ai-fundamentals/5-unde rstand-natural-language-process",
        "references": ""
    },
    {
        "question": ": In Starship Commander game, it uses ______________ to enable players to control the narrative and inte ract with in- game characters and starship systems.",
        "options": [
            "A. Conversational AI",
            "B. Natural language processing (NLP)",
            "C. Responsible AI",
            "D. Chatbots"
        ],
        "correct": "B. Natural language processing (NLP)",
        "explanation": "Explanation Starship Commander, is a virtual realit y (VR) game from Human Interact, that takes place i n a science fiction world. The game uses natural language processing to  enable players to control the narrative and intera ct with in-game characters and starship systems. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/get-st arted- ai- fundamentals/5-understand-natural-language-process",
        "references": ""
    },
    {
        "question": ": Text Analytics service is used to do the following.  Choose the correct option.",
        "options": [
            "A. Extract key phrases",
            "B. Detect entities",
            "C. Evaluate sentiment",
            "D. Translate spoken languages."
        ],
        "correct": "",
        "explanation": "Explanation Text Analytics service can be used to a nalyze text documents and extract key phrases, dete ct entities (such as places, dates, and people), and evaluate sentiment (how positive or negative a document is). Reference  Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
        "references": ""
    },
    {
        "question": ": Which service is used to analyze text documents and  extract key phrases, detect entities, and evaluate sentiment?",
        "options": [
            "A. Text Analytics",
            "B. Language Understanding Intelligent Service (LUIS) C. Speech",
            "D. Translator Text"
        ],
        "correct": "A. Text Analytics",
        "explanation": "Explanation Text Analytics service is used to analy ze text documents and extract key phrases, detect e ntities (such as places, dates, and people), and evaluate sentiment (how pos itive or negative a document is). Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
        "references": ""
    },
    {
        "question": ": Which service is used to translate text between mor e than 60 languages?",
        "options": [
            "A. Language Understanding Intelligent Service (LUIS)",
            "B. Text Analytics",
            "C. Translator Text",
            "D. Speech"
        ],
        "correct": "C. Translator Text",
        "explanation": "Explanation Translator Text service is used to tran slate text between more than 60 languages. Referenc e Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
        "references": ""
    },
    {
        "question": ": Speech service is used to recognize and ________ sp eech, and to _________ spoken languages.",
        "options": [
            "A. Synthesize",
            "B. Analyze",
            "C. Transcribe",
            "D. Translate"
        ],
        "correct": "",
        "explanation": "Explanation Speech service is used to recognize and  synthesize speech, and to translate spoken languag es. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
        "references": ""
    },
    {
        "question": ": Which service is used to recognize and synthesize s peech, and to translate spoken languages. A. Language Understanding Intelligent Service (LUIS)",
        "options": [
            "B. Speech",
            "C. Translator Text",
            "D. Text Analytics"
        ],
        "correct": "B. Speech",
        "explanation": "Explanation Speech service is used to recognize and  synthesize speech, and to translate spoken languag es. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/5-understand-natural-langua ge- process",
        "references": ""
    },
    {
        "question": ": For production, you should create an inference clus ter, which provides an _______________ cluster that provides better scalability and security.",
        "options": [
            "A. Azure Kubernetes Service (AKS)",
            "B. Azure Container Instance (ACI)",
            "C. Azure Inference Clsuter (AIC)",
            "D. Azure Compute Instance (ACI)"
        ],
        "correct": "A. Azure Kubernetes Service (AKS)",
        "explanation": "Explanation For production, you should create an in ference cluster, which provides an Azure Kubernetes Service (AKS) cluster that provides better scalability and securi ty. Reference Link: https://docs.microsoft.com/en-u s/learn/ modules/create- regression-model-azure-machine-learning-designer/in ference-pipeline",
        "references": ""
    },
    {
        "question": ": You are creating a training pipeline for a regressi on model, using a dataset that has multiple numeric  columns in which the values are on different scales. You want to transform the numeric columns so that the values  are all on a similar scale based relative to the minimum and max imum values in each column. Which module should you add to the pipeline?",
        "options": [
            "A. Select Columns in a Dataset",
            "B. Normalize Data",
            "C. Clean Missing Data",
            "D. All of the above"
        ],
        "correct": "",
        "explanation": "Explanation When you need to transform numeric data  to be on a similar scale, use a Normalize Data mod ule. Reference Link: https://docs.microsoft.com/en-us/learn/module s/create-regression-model-azure-machine-learning- designer/inference- pipeline",
        "references": ""
    },
    {
        "question": ": A form of machine learning that is used to predict which category, or class, an item belongs to. Choos e the correct option.",
        "options": [
            "A. Time series forecasting",
            "B. Clustering",
            "C. Classification",
            "D. Regression"
        ],
        "correct": "C. Classification",
        "explanation": "Explanation Classification is a form of machine lea rning that is used to predict which category, or cl ass, an item belongs to. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-classification-model-azure-machi ne- learning- designer/introduction",
        "references": ""
    },
    {
        "question": ": Classification is an example of a __________ techni que in which you train a model using data that incl udes both the features and known values for the label, so that th e model learns to fit the feature combinations to t he label.",
        "options": [
            "A. Semi-supervised machine learning",
            "B. Supervised machine learning",
            "C. Unsupervised machine learning",
            "D. All of the above"
        ],
        "correct": "B. Supervised machine learning",
        "explanation": "Explanation Classification is an example of a super vised machine learning technique in which you train  a model using data that includes both the features and known values fo r the label, so that the model learns to fit the fe ature combinations to the label. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/create-classification-model-azur e- machine-learning- designer/introduction",
        "references": ""
    },
    {
        "question": ": You can use Microsoft ____________ to create classi fication models by using a drag and drop visual int erface, without needing to write any code.",
        "options": [
            "A. Azure Machine Learning Studio",
            "B. Azure Machine Learning designer",
            "C. Microsoft Azure Machine Learning dashboard",
            "D. None of the above"
        ],
        "correct": "B. Azure Machine Learning designer",
        "explanation": "Explanation You can use Microsoft Azure Machine Lea rning designer to create classification models by u sing a drag and drop visual interface, without needing to write any  code. Reference Link: https://docs.microsoft.com/e n- us/learn/modules/create-classification-model-azure- machine-learning-designer/introduction",
        "references": ""
    },
    {
        "question": ": The inference pipeline assumes that new data will m atch the schema of the original training data.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation The inference pipeline assumes that new  data will match the schema of the original trainin g data. Reference Link: https://docs.microsoft.com/en-us/learn/module s/create-regression-model-azure-machine-learning- designer/inference- pipeline",
        "references": ""
    },
    {
        "question": ": What all are the metrics used in Classification pro blems? Choose the correct options.",
        "options": [
            "A. Accuracy",
            "B. Call",
            "C. Precision",
            "D. Recall"
        ],
        "correct": "",
        "explanation": "Explanation Explanation Metrics used in Classification problems : Accuracy, Precision, Recall, F1 Score, AUC Refere nce Link: https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ evaluate- model",
        "references": ""
    },
    {
        "question": ": Why do we split our data into training and validati on sets?",
        "options": [
            "A. Data is split into two sets in order to create tw o models, one model using the training set and a",
            "B. Splitting data into two sets enables you to compa re the labels that the model predicts with the",
            "C. We only need to split our data when we use the Az ure Machine Learning Designer, not in other",
            "D. None of the above"
        ],
        "correct": "B. Splitting data into two sets enables you to compa re the labels that the model predicts with the",
        "explanation": "Explanation We want to test the model created with training data on validation data to see how well th e model performs with data it was not trained on. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/create-regr ession- model-azure- machine-learning-designer/inference-pipeline",
        "references": ""
    },
    {
        "question": ": The ratio of correct predictions (true positives + true negatives) to the total number of predictions.  Choose the correct option.",
        "options": [
            "A. F1 Score",
            "B. Precision",
            "C. Accuracy",
            "D. Recall"
        ],
        "correct": "C. Accuracy",
        "explanation": "Explanation Accuracy: The ratio of correct predicti ons (true positives + true negatives) to the total number of predictions. In other words, what proportion of diabetes prediction s did the model get right? Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": The fraction of positive cases correctly identified  (the number of true positives divided by the numbe r of true positives plus false positives). Choose the correct  option. A. Precision",
        "options": [
            "B. Recall",
            "C. F1 Score",
            "D. Accuracy"
        ],
        "correct": "",
        "explanation": "Explanation Precision: The fraction of positive cas es correctly identified (the number of true positiv es divided by the number of true positives plus false positives). In other words, out of all the patients that the model  predicted as having diabetes, how many are actually diabetic? Reference  Link: https://docs.microsoft.com/en-us/learn/modul es/ create- classification-model-azure-machine-learning-designe r/evaluate-model",
        "references": ""
    },
    {
        "question": ": An overall metric that essentially combines _______ _ and _______ in classification problems.",
        "options": [
            "A. Precision",
            "B. F1 Score",
            "C. Accuracy",
            "D. Recall"
        ],
        "correct": "",
        "explanation": "Explanation F1 Score: An overall metric that essent ially combines precision and recall. Reference Link : https://docs.microsoft.com/en-us/learn/modules/crea te-classification-model-azure-machine-learning-desi gner/ evaluate- model",
        "references": ""
    },
    {
        "question": ": A health clinic use the characteristics of a patien t such as age, weight, blood pressure to predict wh ether the patient is at risk of diabetes. Choose the correct option.",
        "options": [
            "A. Regression",
            "B. Clustering",
            "C. Classification",
            "D. Time series forecasting"
        ],
        "correct": "C. Classification",
        "explanation": "Explanation Explanation Classification is a form of machine lea rning that is used to predict which category, or cl ass, an item belongs to. For example, a health clinic might use the characte ristics of a patient (such as age, weight, blood pr essure, and so on) to predict whether the patient is at risk of diabetes.  In this case, the characteristics of the patient a re the features, and the label is a classification of either 0 or 1, representing non -diabetic or diabetic. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/create-classification-model-azure- machine-learning-designer/introduction",
        "references": ""
    },
    {
        "question": ": Average Precision (AP) is an overall metric that ta kes into account both precision and recall.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Average Precision (AP): An overall metr ic that takes into account both precision and recal l. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
        "references": ""
    },
    {
        "question": ": What percentage of the class predictions made by th e model were correct? Choose the correct evaluation metrics for given example.",
        "options": [
            "A. Recall",
            "B. Precision",
            "C. Mean Absolute Error(MAE)",
            "D. Average Precision (AP)"
        ],
        "correct": "B. Precision",
        "explanation": "Explanation Precision identifies What percentage of  the class predictions made by the model were corre ct. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/2-azure-image-classificat ion",
        "references": ""
    },
    {
        "question": ": To use your model, client application developers ne ed the following information in custom vision model . Choose the appropriate options.",
        "options": [
            "A. Project ID",
            "B. Project Name",
            "C. Model name D. Prediction endpoint"
        ],
        "correct": "",
        "explanation": "Explanation To use your model, client application d evelopers need the following information: Project I D, Prediction endpoint, Prediction key, Model name Reference Link : https://docs.microsoft.com/en-us/learn/modules/cl assify- images- custom-vision/2-azure-image-classification",
        "references": ""
    },
    {
        "question": ": Which workload is used for performing visual search es for specific products in online searches or even , in-store using a mobile device?",
        "options": [
            "A. Image analysis",
            "B. Image processing",
            "C. Image classification",
            "D. Image manipulation"
        ],
        "correct": "C. Image classification",
        "explanation": "Explanation Product identification: performing visu al searches for specific products in online searche s or even, in-store using a mobile device. Reference Link: https://docs .microsoft.com/en-us/learn/modules/classify-images- custom-vision/1- introduction",
        "references": ""
    },
    {
        "question": ": Your organization has an existing frequently asked questions (FAQ) document. You need to create a QnA Maker knowledge base that includes the questions and answ ers from the FAQ with the least possible effort. Wh at should you do?",
        "options": [
            "A. Create an empty knowledge base, and then manually  copy and paste the FAQ entries into it.",
            "B. Import a pre-defined chit-chat data source.",
            "C. Import the existing FAQ document into a new knowl edge base.",
            "D. None",
            "A. 1",
            "B. 0.5",
            "C. 0",
            "D. None"
        ],
        "correct": "B. 0.5",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Read API works best synchronously.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Classification is an example of __ machine learning .",
        "options": [
            "A. Supervised",
            "B. Unsupervised",
            "C. Linear",
            "D. Regression"
        ],
        "correct": "A. Supervised",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": An automobile dealership wants to use historic car sales data to train a machine learning model. The m odel should predict the price of a pre-owned car based on chara cteristics like its age, engine size, and mileage. What kind of machine learning model does the dealership need to create?",
        "options": [
            "A. Supervised",
            "B. Regression C. Unsupervised",
            "D. Linear"
        ],
        "correct": "B. Regression C. Unsupervised",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You wish to upload your custom images for an image classification machine learning service you are cre ating. What options are available to you?",
        "options": [
            "A. Azure machine learning",
            "B. Azure portal",
            "C. Computer Vision",
            "D. Custom Vision Portal"
        ],
        "correct": "D. Custom Vision Portal",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": A model is developed to take medical images as inpu t and decide on whether tumor is benign or malignan t. This is an example of-",
        "options": [
            "A. Regression",
            "B. Linear",
            "C. Classification",
            "D. Supervised"
        ],
        "correct": "C. Classification",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": OCR API works best asynchronously.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Questions in the knowledge base can be assigned ___ _______ to help consolidate questions with the same meaning.",
        "options": [
            "A. None of the above",
            "B. Prepositional phrasing",
            "C. Alternative phrasing",
            "D. Infinitive phrasing"
        ],
        "correct": "C. Alternative phrasing",
        "explanation": "Explanation Questions in the knowledge base can be assigned alternative phrasing to help consolidate questions with the same meaning. Reference Link: https://docs.microsof t.com/en-in/learn/modules/build-faq-chatbot-qna-mak er- azure-bot- service/2-get-started-qna-bot",
        "references": ""
    },
    {
        "question": ": User can use OCR to read text in __________ or to e xtract information from scanned documents such as _________, invoices, or forms.",
        "options": [
            "A. Files",
            "B. Videos",
            "C. Photographs",
            "D. Letters"
        ],
        "correct": "",
        "explanation": "Explanation You can use OCR to read text in photogr aphs (for example, road signs or store fronts) or t o extract information from scanned documents such as letters, invoices, o r forms. Reference Link: https://docs.microsoft.com /en- us/learn/modules/get-started-ai-fundamentals/4-unde rstand-computer-vision",
        "references": ""
    },
    {
        "question": ": A sentiment score may be 0 is in the case where the  wrong language code was used.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation A score may be 0.5 is in the case where  the wrong language code was used. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": The square root of the mean squared difference betw een predicted and true values. Choose the correct o ption.",
        "options": [
            "A. Relative Mean Squared Error (RMSE)",
            "B. Root Mean Squared Error (RMSE)",
            "C. Root Mean Relative Error (RMRE)",
            "D. Root Mean Absolute Error (RMAE)"
        ],
        "correct": "B. Root Mean Squared Error (RMSE)",
        "explanation": "Explanation Root Mean Squared Error (RMSE): The squ are root of the mean squared difference between predicted and true values. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/create-regression-model-azure- machine-learning- designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": To train a regression model, you need a dataset tha t includes historical _________ and known _____ val ues.",
        "options": [
            "A. Objects",
            "B. Label",
            "C. Features",
            "D. Numeric"
        ],
        "correct": "",
        "explanation": "Explanation To train a regression model, you need a  dataset that includes historical features (charact eristics of the entity for which you want to make a prediction) and known labe l values (the numeric value that you want to train a model to predict). Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/explore-data",
        "references": ""
    },
    {
        "question": ": In which machine learning technique the object bein g classified is an image, such as a photograph?",
        "options": [
            "A. Image Segmentation",
            "B. Image Classification C. Object Detection",
            "D. None of the above"
        ],
        "correct": "B. Image Classification C. Object Detection",
        "explanation": "Explanation Image classification is a machine learn ing technique in which the object being classified is an image, such as a photograph. Reference Link: https://docs.microsoft. com/en-us/learn/modules/classify-images-custom-visi on/1a- overview- classification",
        "references": ""
    },
    {
        "question": ": Microsoft Azure offers both __________ and ________  capabilities through the Speech cognitive service.",
        "options": [
            "A. Speech analytics",
            "B. Speech recognition",
            "C. Speech translation",
            "D. Speech synthesis"
        ],
        "correct": "",
        "explanation": "Explanation Microsoft Azure offers both speech reco gnition and speech synthesis capabilities through t he Speech cognitive service. Reference Link: https://docs.microsoft.com /en-in/learn/modules/recognize-synthesize-speech/2- get- started-azure",
        "references": ""
    },
    {
        "question": ": A machine learning model could be trained by applyi ng an algorithm to these measurements that calculat es the most likely species of the flower. Choose the correct op tion for given example.",
        "options": [
            "A. Regression",
            "B. None of the above",
            "C. Classification",
            "D. Clustering"
        ],
        "correct": "C. Classification",
        "explanation": "Explanation You can use a machine learning classifi cation technique to predict which category, or clas s, something belongs to. For example, the features of a flower might inc lude the measurements of its petals, stem, sepals, and other quantifiable characteristics. A machine learning model could be trained by applying an algorithm to these measureme nts that calculates the most likely species of the flower - its class. Reference Link: https://docs.microsoft.com/en-us/le arn/ modules/classify- images-custom-vision/1a-overview-classification",
        "references": ""
    },
    {
        "question": ": Paid subscription version of the Form Recognizer su pports up to _ pages and a maximum of _ lines per p age.",
        "options": [
            "A. 400 Pages",
            "B. 100 Pages",
            "C. 200 Pages",
            "D. 300 Pages"
        ],
        "correct": "A. 400 Pages",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": What type of compute resource do you need to deploy  AKS in Azure Machine Learning?",
        "options": [
            "A. Inference Cluster",
            "B. Compute Node",
            "C. Compute Custer",
            "D. Attachment Compute"
        ],
        "correct": "B. Compute Node",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Which service is used to extract information from s canned forms and invoices?",
        "options": [
            "A. None of the above",
            "B. Custom Vision",
            "C. Form Recognizer",
            "D. Optical character recognition ( OCR )",
            "A. Custom Vision",
            "B. Face",
            "C. Face API",
            "D. Computer Vision"
        ],
        "correct": "B. Face",
        "explanation": "Explanation The Face service enables you to build f ace detection and facial recognition solutions. Ref erence Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": The pipeline starts with the _______ from which you  want to train the model.",
        "options": [
            "A. Entities",
            "B. Features",
            "C. Objects",
            "D. Dataset"
        ],
        "correct": "D. Dataset",
        "explanation": "Explanation The pipeline starts with the dataset fr om which you want to train the model. Reference Lin k: https://docs.microsoft.com/en-us/learn/modules/crea te-regression-model-azure-machine-learning-designer / explore-data",
        "references": ""
    },
    {
        "question": ": The concept of evaluating the text of a document, o r documents, and then identifying the main talking points of the document(s). Choose the correct term.",
        "options": [
            "A. Key extraction",
            "B. Phrase extraction",
            "C. Text extraction",
            "D. Key phrase extraction"
        ],
        "correct": "D. Key phrase extraction",
        "explanation": "Explanation Key phrase extraction is the concept of  evaluating the text of a document, or documents, a nd then identifying the main talking points of the document(s). Referen ce Link: https://docs.microsoft.com/en-in/learn/mod ules/ analyze-text- with-text-analytics-service/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": Machine learning models must be trained with existi ng data.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation Machine learning models must be trained  with existing data. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/dat a",
        "references": ""
    },
    {
        "question": ": Which targets are cloud-based resources on which yo u can run model training and data exploration proce sses?",
        "options": [
            "A. None of the above",
            "B. Compute",
            "C. Inference",
            "D. Attached"
        ],
        "correct": "B. Compute",
        "explanation": "Explanation Compute targets are cloud-based resourc es on which you can run model training and data exploration processes. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/create-compute",
        "references": ""
    },
    {
        "question": ": A specialized form of object detection that locates  human faces in an image. Choose the correct option .",
        "options": [
            "A. Image analysis",
            "B. Image classification",
            "C. Semantic segmentation",
            "D. Face detection"
        ],
        "correct": "D. Face detection",
        "explanation": "Explanation Face detection is a specialized form of  object detection that locates human faces in an im age. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": A bank wants to use historic loan repayment records  to categorize loan applications as low-risk or hig h-risk based on characteristics like the loan amount, the income of  the borrower, and the loan period. What kind of ma chine learning model should the bank use automated machine learnin g to create?",
        "options": [
            "A. Classification",
            "B. Time series forecasting",
            "C. None of the above",
            "D. Regression"
        ],
        "correct": "A. Classification",
        "explanation": "Explanation To predict a category, or class, use a classification model. Reference Link: https:// docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/dat a",
        "references": ""
    },
    {
        "question": ": The ________________ will be the value returned, al ong with the language code. Choose the correct opti on.",
        "options": [
            "A. Predominant language",
            "B. Expressive language",
            "C. All of the above",
            "D. Dominant language"
        ],
        "correct": "A. Predominant language",
        "explanation": "Explanation The predominant language will be the va lue returned, along with the language code. Referen ce Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": A score of 0.5 might indicate that the sentiment of  the text is _________, and could result from text that does not have sufficient context to discern a sentiment or insuff icient phrasing.",
        "options": [
            "A. Neutral",
            "B. Indeterminate",
            "C. Positive D. Determinate"
        ],
        "correct": "B. Indeterminate",
        "explanation": "Explanation A score of 0.5 might indicate that the sentiment of the text is indeterminate, and could r esult from text that does not have sufficient context to discern a sentiment or insufficient phrasing. Reference Link: https:// docs.microsoft.com/en- in/learn/modules/analyze-text-with-text-analytics-s ervice/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": A relative metric between 0 and 1 based on the squa re of the differences between predicted and true va lues. Choose the correct option.",
        "options": [
            "A. Root Mean Squared Error (RMSE)",
            "B. Relative Absolute Error (RAE)",
            "C. Mean Absolute Error (MAE)",
            "D. Relative Squared Error (RSE)"
        ],
        "correct": "D. Relative Squared Error (RSE)",
        "explanation": "Explanation Relative Squared Error (RSE): A relativ e metric between 0 and 1 based on the square of the differences between predicted and true values. Reference Link: https://docs.microsoft.com/en-us/learn/modules/crea te- regression- model-azure-machine-learning-designer/evaluate-mode l",
        "references": ""
    },
    {
        "question": ": To use the Azure Machine Learning designer, you cre ate a ___________ that you will use to train a mach ine learning model.",
        "options": [
            "A. chain",
            "B. pipeline",
            "C. Roles",
            "D. Experiments"
        ],
        "correct": "B. pipeline",
        "explanation": "Explanation To use the Azure Machine Learning desig ner, you create a pipeline that you will use to tra in a machine learning model. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/create-regression-model-azure- machine-learning- designer/explore-data",
        "references": ""
    },
    {
        "question": ": You wish to develop an application which can take v erbal commands. What Azure service should you provision?",
        "options": [
            "A. Azure Text Analytics",
            "B. Speech",
            "C. None of the above",
            "D. LUIS"
        ],
        "correct": "B. Speech",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": For each document submitted to it, the language ser vice will detect the below tasks. Choose the correc t options.",
        "options": [
            "A. The ISO 6391 language code (for example, \"en\")",
            "B. The language name (for example \"English\")",
            "C. A score indicating a level of confidence in the l anguage detection",
            "D. Sentiments like positive or negative"
        ],
        "correct": "",
        "explanation": "Explanation For each document submitted to it, the language service will detect the following: The lan guage name (for example \"English\"). The ISO 6391 language code (for  example, \"en\"). A score indicating a level of conf idence in the language detection. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/analyze-text-with-t ext- analytics- service/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": User can create solutions that combine machine lear ning models to extract information from images, inc luding \"tags\" that could help catalog the image or even de scriptive captions that summarize the scene shown i n the image. Choose the correct option.",
        "options": [
            "A. Image classification",
            "B. Image analysis",
            "C. Semantic segmentation",
            "D. Object detection Correct Answer: B"
        ],
        "correct": "",
        "explanation": "Explanation You can create solutions that combine m achine learning models with advanced image analysis techniques to extract information from images, including \"tags\" t hat could help catalog the image or even descriptiv e captions that summarize the scene shown in the image. Reference L ink: https://docs.microsoft.com/en-us/learn/modules /get- started-ai- fundamentals/4-understand-computer-vision",
        "references": ""
    },
    {
        "question": ": Given example, the following restaurant review coul d be analyzed for sentiment. \"We had dinner at this restaurant last night and the first thing I noticed was how co urteous the staff was. We were greeted in a friendl y manner and taken to our table right away. The table was clean,  the chairs were comfortable, and the food was amaz ing.\"",
        "options": [
            "A. 0.9",
            "B. 1",
            "C. 0.5",
            "D. 0"
        ],
        "correct": "A. 0.9",
        "explanation": "Explanation The sentiment score for the review migh t be around 0.9, indicating a positive sentiment. R eference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": A user support bot solution on Microsoft Azure is c reated using a combination of below two core techno logies?",
        "options": [
            "A. QnA Maker",
            "B. Azure Bot Service",
            "C. All of the above",
            "D. Azure QnA Bot Service",
            "A. Algorithm works better when we use data unchanged",
            "B. It makes no difference. No risk involved",
            "C. Smaller values in data may lead to higher bias",
            "D. Larger values in data may lead to higher bias"
        ],
        "correct": "D. Larger values in data may lead to higher bias",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The language detection service will focus on the do minant language in the text.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation The language detection service will foc us on the predominant language in the text. Referen ce Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": If you consider the concept of `Describing an Image ' of Computer Vision, which of the following are co rrect:",
        "options": [
            "A. Ascending Order",
            "B. Descending Order"
        ],
        "correct": "B. Descending Order",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The Face service enables you to build _________ and  __________ solutions.",
        "options": [
            "A. None of the above",
            "B. Face recognition",
            "C. Face detection",
            "D. Object detection Correct Answer: BC"
        ],
        "correct": "",
        "explanation": "Explanation The Face service enables you to build f ace detection and facial recognition solutions. Ref erence Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": Some potential uses for image classification includ e following things. Choose the correct options.",
        "options": [
            "A. Medical diagnosis",
            "B. Disaster investigation",
            "C. Face detection",
            "D. Product identification"
        ],
        "correct": "",
        "explanation": "Explanation Some potential uses for image classific ation include: Product identification, Disaster inv estigation, Medical diagnosis Reference Link: https://docs.microsoft.co m/en-us/learn/modules/classify-images-custom-vision /1- introduction",
        "references": ""
    },
    {
        "question": ": Users can submit questions to the bot through any o f its channels, but can not receive an appropriate answer from the knowledge base on which the bot is based.",
        "options": [
            "A. FALSE",
            "B. TRUE"
        ],
        "correct": "A. FALSE",
        "explanation": "Explanation Users can submit questions to the bot t hrough any of its channels, and receive an appropri ate answer from the knowledge base on which the bot is based. Reference  Link: https://docs.microsoft.com/en-in/learn/modul es/ build-faq- chatbot-qna-maker-azure-bot-service/2-get-started-q na-bot",
        "references": ""
    },
    {
        "question": ": An item to which an utterance refers. For example, fan and light in the utterances. Choose the correct  option.",
        "options": [
            "A. Intents B. Utterances",
            "C. Entities",
            "D. Objects"
        ],
        "correct": "C. Entities",
        "explanation": "Explanation An entity is an item to which an uttera nce refers. You can think of the fan and light enti ties as being specific instances of a general device entity. For example, fan and light in the following utterances: \"Switch the fan on.\" \"Turn on the light.\" Reference Link: https://docs.microsoft.com/ en-in/learn/modules/recognize-synthesize-speech/2-g et- started-azure",
        "references": ""
    },
    {
        "question": ": To create a knowledge base, you must first provisio n a _________ resource in your Azure subscription.",
        "options": [
            "A. QnA Maker",
            "B. All of the above",
            "C. Azure Bot Service",
            "D. Azure QnA Bot Service"
        ],
        "correct": "A. QnA Maker",
        "explanation": "Explanation To create a knowledge base, you must fi rst provision a QnA Maker resource in your Azure subscription. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/build-faq-chatbot-qna-maker-azure-bot- service/2-get- started-qna-bot",
        "references": ""
    },
    {
        "question": ": A traffic monitoring solution might overlay traffic  images with \"mask\" layers to highlight different v ehicles using specific colors. Choose the correct option.",
        "options": [
            "A. Object detection",
            "B. Image classification",
            "C. Image analysis",
            "D. Semantic segmentation"
        ],
        "correct": "D. Semantic segmentation",
        "explanation": "Explanation Semantic segmentation is an advanced ma chine learning technique in which individual pixels  in the image are classified according to the object to which they be long. For example, a traffic monitoring solution mi ght overlay traffic images with \"mask\" layers to highlight different ve hicles using specific colors. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": Choose the correct regression performance metrics f rom the following.",
        "options": [
            "A. Root Mean Squared Error (RMSE)",
            "B. Mean Relative Error (MRE)",
            "C. Mean Absolute Error (MAE)",
            "D. Relative Squared Error (RSE)"
        ],
        "correct": "",
        "explanation": "Explanation Mean Absolute Error (MAE), Root Mean Sq uared Error (RMSE), Relative Absolute Error (RAE) a re the following regression performance metrics. Reference  Link: https://docs.microsoft.com/en-us/learn/modul es/ create- regression-model-azure-machine-learning-designer/ev aluate-model",
        "references": ""
    },
    {
        "question": ": A common workload in (AI) applications which harnes ses the predictive power of machine learning to ena ble AI systems to identify real-world items based on image s. Choose the correct option.",
        "options": [
            "A. Image manipulation",
            "B. Image classification",
            "C. Image processing",
            "D. Image analysis"
        ],
        "correct": "B. Image classification",
        "explanation": "Explanation Image classification is a common worklo ad in artificial intelligence (AI) applications. It  harnesses the predictive power of machine learning to enable AI systems to i dentify real-world items based on images. Reference  Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/1-introduction",
        "references": ""
    },
    {
        "question": ": Which service is used to train custom image classif ication and object detection models using your own images?",
        "options": [
            "A. Computer Vision",
            "B. None of the above",
            "C. Face API",
            "D. Custom Vision Correct Answer: D"
        ],
        "correct": "",
        "explanation": "Explanation Custom Vision is the service used to tr ain custom image classification and object detectio n models using your own images. Reference Link: https://docs.microsoft. com/en-us/learn/modules/get-started-ai-fundamentals /4- understand- computer-vision",
        "references": ""
    },
    {
        "question": ": Face detection can be combined with __________ and ___________ techniques to infer details such as age and emotional state; and even recognize individuals bas ed on their facial features. Choose the correct opt ion.",
        "options": [
            "A. Facial geometry analysis",
            "B. Appearance geometry analysis",
            "C. Classification",
            "D. Regression"
        ],
        "correct": "",
        "explanation": "Explanation Face detection can be combined with cla ssification and facial geometry analysis techniques  to infer details such as age and emotional state; and even recognize indi viduals based on their facial features. Reference L ink: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": Computer vision is the best Azure resource for dete cting, analyzing and working with Faces.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Once you provision a QnA Maker resource, you can us e the QnA Maker portal to create a ________ that consists of question-and-answer pairs.",
        "options": [
            "A. Dataset",
            "B. Historical data",
            "C. Database D. Knowledge base"
        ],
        "correct": "",
        "explanation": "Explanation After provisioning a QnA Maker resource , you can use the QnA Maker portal to create a know ledge base that consists of question-and-answer pairs. Reference Li nk: https://docs.microsoft.com/en-in/learn/modules/ build- faq-chatbot- qna-maker-azure-bot-service/2-get-started-qna-bot",
        "references": ""
    },
    {
        "question": ": In many cases, a knowledge base is created using a combination of all of these techniques; starting wi th a base dataset of questions and answers from an existing F AQ document, adding common conversational exchanges from a chit-chat source, and extending the knowledge base with additional manual entries.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation In many cases, a knowledge base is crea ted using a combination of all of these techniques; starting with a base dataset of questions and answers from an existing F AQ document, adding common conversational exchanges from a chit- chat source, and extending the knowledge base with additional manual entries. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/2-get-sta rted- qna-bot",
        "references": ""
    },
    {
        "question": ": Most modern image classification solutions are base d on ______ techniques that make use of __________ to uncover patterns in the pixels that correspond to particula r classes.",
        "options": [
            "A. Recurrent neural network (RNN)",
            "B. Deep Learning",
            "C. Convolutional neural networks (CNNs)",
            "D. Machine Learning"
        ],
        "correct": "",
        "explanation": "Explanation Most modern image classification soluti ons are based on deep learning techniques that make  use of convolutional neural networks (CNNs) to uncover pat terns in the pixels that correspond to particular c lasses. Training an effective CNN is a complex task that requires consi derable expertise in data science and machine learn ing. Reference Link: https://docs.microsoft.com/en-us/learn/modules/clas sify-images-custom-vision/1a-overview-classificatio n",
        "references": ""
    },
    {
        "question": ": A technique used to detect and read text in images.  Choose the correct option.",
        "options": [
            "A. Intelligent Character Recognition ( ICR )",
            "B. None of the above",
            "C. Optical mark recognition ( OMR )",
            "D. Optical character recognition ( OCR )"
        ],
        "correct": "D. Optical character recognition ( OCR )",
        "explanation": "Explanation Optical character recognition is a tech nique used to detect and read text in images. Refer ence Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": Image classification can be used for the following use cases",
        "options": [
            "A. Custom",
            "B. Compute Node",
            "C. Object Detection",
            "D. Comupter Vision"
        ],
        "correct": "C. Object Detection",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Performance metrics which calculates average differ ence between predicted values and true values. The lower this value is, the better the model is predicting. Choos e the correct option.",
        "options": [
            "A. Root Mean Squared Error (RMSE)",
            "B. Mean Absolute Error (MAE)",
            "C. Relative Squared Error (RSE)",
            "D. Mean Relative Error (MRE)"
        ],
        "correct": "B. Mean Absolute Error (MAE)",
        "explanation": "Explanation The average difference between predicte d values and true values. This value is based on th e same units as the label. The lower this value is, the better the mode l is predicting. Reference Link: https://docs.micro soft.com/en- us/learn/modules/create-regression-model-azure-mach ine-learning-designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": You want to train a model that classifies images of  dogs and cats based on a collection of your own di gital photographs. Which Azure service should you use?",
        "options": [
            "A. Custom Vision",
            "B. Computer Vision",
            "C. Azure Machine Learning",
            "D. Azure Bot Service"
        ],
        "correct": "A. Custom Vision",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Common techniques used to train image classificatio n models have been encapsulated into the ________ cognitive service , making it easy to train a model and publi sh it as a software service with minimal knowledge of deep learning techniques.",
        "options": [
            "A. Image Segmentation",
            "B. Custom Vision",
            "C. Image classification",
            "D. Object Detection"
        ],
        "correct": "B. Custom Vision",
        "explanation": "Explanation Common techniques used to train image c lassification models have been encapsulated into th e Custom Vision cognitive service in Microsoft Azure; making it eas y to train a model and publish it as a software ser vice with minimal knowledge of deep learning techniques. You can use the Custom Vision cognitive service to train image classification models and deploy them as services for applications  to use.",
        "references": ""
    },
    {
        "question": ": You can use Microsoft Azure Machine Learning design er to create ___________ models by using a drag and drop visual interface, without needing to write any code .",
        "options": [
            "A. None of the above B. Regression",
            "C. Classification",
            "D. Time series forecasting"
        ],
        "correct": "",
        "explanation": "Explanation You can use Microsoft Azure Machine Lea rning designer to create regression models by using  a drag and drop visual interface, without needing to write any code . Reference Link: https://docs.microsoft.com/en-us/ learn/ modules/create- regression-model-azure-machine-learning-designer/in troduction",
        "references": ""
    },
    {
        "question": ": The Computer Vision service can not detect image ty pes.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation The Computer Vision service can detect image types, for example, identifying clip art imag es or line drawings. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/analyze-images-computer-vision/2-image- analysis-azure",
        "references": ""
    },
    {
        "question": ": When RMSE compared to the MAE, a larger difference indicates greater variance in the individual errors .",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation When RMSE compared to the MAE, a larger  difference indicates greater variance in the indiv idual errors. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/evaluate-model",
        "references": ""
    },
    {
        "question": ": What is used to inform the service which language t he text is in? A. Language name",
        "options": [
            "B. Language code",
            "C. All of the above",
            "D. Language ID"
        ],
        "correct": "B. Language code",
        "explanation": "Explanation A language code (such as \"en\" for Engli sh, or \"fr\" for French) is used to inform the servi ce which language the text is in. Reference Link: https://docs.microsoft. com/en-in/learn/modules/analyze-text-with-text-anal ytics- service/2-get- started-azure",
        "references": ""
    },
    {
        "question": ": A list of words in a sentence that has no structure , could result in an _________ score.",
        "options": [
            "A. 0.1",
            "B. Indeterminate",
            "C. 0",
            "D. 0.9"
        ],
        "correct": "B. Indeterminate",
        "explanation": "Explanation A list of words in a sentence that has no structure, could result in an indeterminate scor e. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": OCR API works best synchronously.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": It's common practice to train the model using a ___ ______, while holding back some data with which to test the trained model.",
        "options": [
            "A. Whole data B. Multiple datasets",
            "C. All of the above",
            "D. Subset of the data"
        ],
        "correct": "D. Subset of the data",
        "explanation": "Explanation It's common practice to train the model  using a subset of the data, while holding back som e data with which to test the trained model. Reference Link: https://doc s.microsoft.com/en-us/learn/modules/create-regressi on- model-azure- machine-learning-designer/create-training-pipeline",
        "references": ""
    },
    {
        "question": ": You want to use the Text Analytics service to deter mine the key talking points in a text document. Whi ch feature of the service should you use?",
        "options": [
            "A. Key phrase extraction",
            "B. Entity detection",
            "C. None",
            "D. Sentiment analysis"
        ],
        "correct": "A. Key phrase extraction",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": An automobile dealership wants to use historic car sales data to train a machine learning model. The m odel should predict the price of a pre-owned car based on its m ake, model, engine size, and mileage. What kind of machine learning model should the dealership use automated machine learning to create?",
        "options": [
            "A. None of the above",
            "B. Classification",
            "C. Time series forecasting",
            "D. Regression",
            "A. Length of entities",
            "B. Total amount of text for the language compared to  other languages in the text",
            "C. Length of phrases",
            "D. Length of objects"
        ],
        "correct": "D. Regression",
        "explanation": "Explanation The language service uses an algorithm to determine the predominant language, such as leng th of phrases or total amount of text for the language compared to o ther languages in the text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": If you pass text in French but tell the service the  language code is en for English, the service will return a score of precisely _________.",
        "options": [
            "A. 0.1",
            "B. 0.5",
            "C. 0.9",
            "D. Indeterminate"
        ],
        "correct": "B. 0.5",
        "explanation": "Explanation If you pass text in French but tell the  service the language code is en for English, the s ervice will return a score of precisely 0.5. Reference Link: https://docs.micr osoft.com/en-in/learn/modules/analyze-text-with-tex t- analytics-service/2- get-started-azure",
        "references": ""
    },
    {
        "question": ": You want to use automated machine learning to train  a regression model with the best possible R2 score . How should you configure the automated machine learning experi ment?",
        "options": [
            "A. Disable featurization",
            "B. Enable featurization",
            "C. Set the Primary metric to R2 score",
            "D. Block all algorithms other than GradientBoosting"
        ],
        "correct": "",
        "explanation": "Explanation The primary metric determines the metri c used to evaluate the best performing model. Refer ence Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
        "references": ""
    },
    {
        "question": ": The simplest approach is to use a general Cognitive  Services resource for both ______ and _________.",
        "options": [
            "A. Deployment",
            "B. Training",
            "C. Prediction",
            "D. Processing"
        ],
        "correct": "",
        "explanation": "Explanation The simplest approach is to use a gener al Cognitive Services resource for both training an d prediction. This means you only need to concern yourself with one en dpoint (the HTTP address at which your service is h osted) and key (a secret value used by client applications to authent icate themselves). Reference Link: https:// docs.microsoft.com/en- us/learn/modules/classify-images-custom-vision/1a-o verview-classification",
        "references": ""
    },
    {
        "question": ": You are developing an application that must take En glish input from a microphone and generate a real-t ime text- based transcription in Hindi. Which service should you use?",
        "options": [
            "A. Text Analytics",
            "B. Translator Text",
            "C. QnA Maker",
            "D. Speech"
        ],
        "correct": "B. Translator Text",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Regression is an example of a ____________ machine learning technique in which you train a model using data that includes both the ____________ and known values for  the label, so that the model learns to fit the fea ture combinations to the label. A. Features",
        "options": [
            "B. Supervised",
            "C. Unsupervised",
            "D. Entities"
        ],
        "correct": "",
        "explanation": "Explanation Regression is an example of a supervise d machine learning technique in which you train a m odel using data that includes both the features and known values for the  label, so that the model learns to fit the feature combinations to the label. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/create-regression-model-azure-machine- learning- designer/introduction",
        "references": ""
    },
    {
        "question": ": What is the typical minimum number of Compute Clust er nodes recommended for training in a Production environment?",
        "options": [
            "A. 1",
            "B. 2",
            "C. 0",
            "D. 3"
        ],
        "correct": "B. 2",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": A process where you evaluate different aspects of a  document or phrase, in order to gain insights into  the content of that text.",
        "options": [
            "A. Analyzing objects",
            "B. Analyzing Text",
            "C. Analyzing entities",
            "D. Synthesizing text",
            "A. Azure Machine Learning",
            "B. QnA Maker",
            "C. Text Analytics",
            "D. None of the above"
        ],
        "correct": "A. Azure Machine Learning",
        "explanation": "Explanation Azure Machine Learning enables you to t rain a predictive model from the existing data. Ref erence Link: https://docs.microsoft.com/en-us/learn/module s/get-started-ai-fundamentals/2-understand-machine- learn",
        "references": ""
    },
    {
        "question": ": Anomaly detector is stateful.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You need to deliver a support bot for internal use in your organization. Some users want to be able to  submit questions to the bot using Microsoft Teams, others want to use a web chat interface on an internal web  site. What should you do?",
        "options": [
            "A. None of the above",
            "B. Create a knowledge base. Then create two bots tha t use the same knowledge base - one bot",
            "C. Create a knowledge base. Then create a bot for th e knowledge base and connect the Web Chat and",
            "D. Create two knowledge bases with the same question  and answer pairs. Then create a bot for each"
        ],
        "correct": "C. Create a knowledge base. Then create a bot for th e knowledge base and connect the Web Chat and",
        "explanation": "Explanation The Microsoft Teams channel enables you r bot to receive and respond to messages in Microso ft Teams, and the Web Chat channel enables interaction s through a web chat interface. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
        "references": ""
    },
    {
        "question": ": To use the Computer Vision service, you need to cre ate a resource for it in your Azure subscription. C hoose the appropriate resource types from the following.",
        "options": [
            "A. Computer Vision",
            "B. Advance Computer Vision",
            "C. Custom Vision",
            "D. Cognitive Services"
        ],
        "correct": "",
        "explanation": "Explanation To use the Computer Vision service, you  need to create a resource for it in your Azure subscription. You can use either of the following resource types:  Computer Vision, Cognitive Services Reference Link : https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": A racing car telemetry system that uses sensors to proactively warn engineers about potential mechanic al failures before they happen. Choose the correct opt ion.",
        "options": [
            "A. Clustering",
            "B. Regression",
            "C. Classification",
            "D. Anomaly detection"
        ],
        "correct": "D. Anomaly detection",
        "explanation": "Explanation By using anomaly detection - a machine learning based technique that analyzes data over ti me and identifies unusual changes.",
        "references": ""
    },
    {
        "question": ": Choose this resource type if you only plan to use N LP services, or want to manage access and billing f or the resource separately from other services.",
        "options": [
            "A. Language resource",
            "B. Text analytics service",
            "C. Language cognitive service",
            "D. Text Language service"
        ],
        "correct": "A. Language resource",
        "explanation": "Explanation A Language resource - choose this resou rce type if you only plan to use natural language processing services, or if you want to manage access and billi ng for the resource separately from other services. Reference Link: https://docs.microsoft.com/en-in/learn/module s/analyze-text-with-text-analytics-service/2-get-st arted- azure",
        "references": ""
    },
    {
        "question": ": Conversations typically take the form of messages e xchanged in turns; and one of the most common kinds  of _______ is a question followed by an answer.",
        "options": [
            "A. Transactional exchange",
            "B. Conversational exchange",
            "C. None of the above",
            "D. Natural language exchange"
        ],
        "correct": "B. Conversational exchange",
        "explanation": "Explanation Conversations typically take the form o f messages exchanged in turns; and one of the most common kinds of conversational exchange is a questi on followed by an answer. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
        "references": ""
    },
    {
        "question": ": Define the sequence of steps performed by Azure Mac hine Learning. Choose the correct options from following.",
        "options": [
            "A. Prepare the data",
            "B. Deploy a predictive service",
            "C. None of the above",
            "D. Train a model"
        ],
        "correct": "",
        "explanation": "Explanation Azure Machine Learning is a cloud-based  service that helps simplify some of the tasks and reduce the time it takes to prepare data, train a model, a nd deploy a predictive service. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/what-is-ml",
        "references": ""
    },
    {
        "question": ": A cognitive service in Microsoft Azure that provide s pre-built computer vision capabilities. Choose th e correct option.",
        "options": [
            "A. Computer Vision service",
            "B. Custom vision",
            "C. All of the above D. Advance Computer Vision"
        ],
        "correct": "A. Computer Vision service",
        "explanation": "Explanation The Computer Vision service is a cognit ive service in Microsoft Azure that provides pre-bu ilt computer vision capabilities. The service can analy ze images, and return detailed information about an  image and the objects it depicts. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/analyze-ima ges- computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": Which algorithms can be used to normalize words bef ore counting them?",
        "options": [
            "A. Lemmatization",
            "B. N-Grams",
            "C. M-Grams",
            "D. Stemming"
        ],
        "correct": "",
        "explanation": "Explanation Applying stemming or lemmatization algo rithms to normalize words before counting them - fo r example, so that words like \"power\", \"powered\", and  \"powerful\" are interpreted as being the same word. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/analyze-text-with-text-analytics-servic e/1- introduction",
        "references": ""
    },
    {
        "question": ": Which compute resources are scalable clusters of vi rtual machines for on-demand processing of experime nt code?",
        "options": [
            "A. Kubernetes Clusters",
            "B. Inference Clusters",
            "C. Managed Cluster",
            "D. Compute Clusters"
        ],
        "correct": "D. Compute Clusters",
        "explanation": "Explanation Compute Clusters: Scalable clusters of virtual machines for on-demand processing of experi ment code. Reference Link: https://docs.microsoft.com/en -us/learn/modules/use-automated-machine- learning/create-compute",
        "references": ""
    },
    {
        "question": ": In Microsoft Azure, the ________ service can help s implify application development by using pre-traine d models that can determine the language of a document or te xt",
        "options": [
            "A. Text Language service",
            "B. Language API service",
            "C. Language cognitive service",
            "D. Text analytics service"
        ],
        "correct": "C. Language cognitive service",
        "explanation": "Explanation In Microsoft Azure, the Language cognit ive service can help simplify application developme nt by using pre-trained models that can determine the lan guage of a document or text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
        "references": ""
    },
    {
        "question": ": Organizations are turning to artificial intelligenc e (AI) solutions that make use of AI agents, common ly known as _______ to provide a first-line of automated sup port through the full range of channels that we use  to communicate.",
        "options": [
            "A. QnA section",
            "B. Feedback section",
            "C. About us",
            "D. Bots"
        ],
        "correct": "D. Bots",
        "explanation": "Explanation Organizations are turning to artificial  intelligence (AI) solutions that make use of AI ag ents, commonly known as bots to provide a first-line of a utomated support through the full range of channels  that we use to communicate. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/build-faq-chatbot-q na- maker-azure-bot-service/1-introduction/",
        "references": ""
    },
    {
        "question": ": __ can be used for medical imaging diagnosis.",
        "options": [
            "A. Image Classification",
            "B. Custom Vision",
            "C. Cognitive Services",
            "D. Computer Vision"
        ],
        "correct": "A. Image Classification",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": "You can use the ___________ capabilities in the Lan guage service to detect the language for each of th e reviews from various applications.",
        "options": [
            "A. Language detection",
            "B. Text Language",
            "C. Language API",
            "D. Text analytics"
        ],
        "correct": "D. Text analytics",
        "explanation": "Explanation You can use the text analytics capabili ties in the Language service to detect the language  for each of these reviews; and it might respond with the follow ing results. Document Language ISO 6391 Code Score Review 1 English en 1.0 Review 2 Spanish es 1.0 Review 3 E nglish en 0.9 Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": Extending frequency analysis to multi-term phrases,  commonly known as M-grams.",
        "options": [
            "A. FALSE",
            "B. TRUE"
        ],
        "correct": "A. FALSE",
        "explanation": "Explanation Extending frequency analysis to multi-t erm phrases, commonly known as N-grams (a two-word phrase is a bi-gram, a three-word phrase is a tri-g ram, and so on). Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
        "references": ""
    },
    {
        "question": ": What Is the typical minimum number of Compute Clust er nodes recommended for training in a Production environment?",
        "options": [
            "A. 1",
            "B. 3",
            "C. 2",
            "D. 0",
            "A. None of the above",
            "B. Azure Bot Service",
            "C. Custom Vision",
            "D. Computer Vision"
        ],
        "correct": "C. Custom Vision",
        "explanation": "Explanation Custom Vision enables you to train an i mage classification model based on your own images. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/4-understan d- computer-vision",
        "references": ""
    },
    {
        "question": ": You want to use the Text Analytics service to deter mine the key talking points in a text document. Whi ch feature of the service should you use?",
        "options": [
            "A. Key phrase extraction",
            "B. Sentiment analysis",
            "C. None",
            "D. Entity detection"
        ],
        "correct": "A. Key phrase extraction",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": This service can return what is known as bounding b ox coordinates in computer vision. Choose the corre ct option.",
        "options": [
            "A. Tagging visual features",
            "B. Describing an image",
            "C. Detecting brands",
            "D. Object detection"
        ],
        "correct": "D. Object detection",
        "explanation": "Explanation The object detection capability is simi lar to tagging, in that the service can identify co mmon objects; but rather than tagging, or providing tags for the recognized objects only, this service can also retu rn what is known as bounding box coordinates. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze- images-computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": A cloud service that you can use to train and manag e machine learning models. Choose the correct optio n.",
        "options": [
            "A. Azure Machine Learning",
            "B. Azure Automated Learning",
            "C. Azure AI Learning",
            "D. Azure Deep Learning"
        ],
        "correct": "A. Azure Machine Learning",
        "explanation": "Explanation Azure Machine Learning is a cloud servi ce that you can use to train and manage machine lea rning models. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/use-automated-machine- learning/introduction",
        "references": ""
    },
    {
        "question": ": Which service is used to suggest class and bounding  boxes you add to training set after an initial dat aset:",
        "options": [
            "A. Smart tagging",
            "B. None",
            "C. Auto-tagging",
            "D. tag smart"
        ],
        "correct": "D. tag smart",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Where do you manage the compute targets? Choose the  correct option.",
        "options": [
            "A. Azure Machine Learning Designer",
            "B. Azure Machine Learning Dashboard",
            "C. Azure Machine Learning service",
            "D. Azure Machine Learning studio",
            "A. None of the above",
            "B. Statistical analysis of terms used in the text.",
            "C. Extending frequency analysis to multi-term phrase s, commonly known as N-grams",
            "D. Applying stemming or lemmatization algorithms to normalize words before counting them"
        ],
        "correct": "D. Azure Machine Learning studio",
        "explanation": "Explanation There are some commonly used techniques  that can be used to build software to analyze text , including: Statistical analysis of terms used in th e text. Extending frequency analysis to multi-term phrases, commonly known as N-grams. Applying stemming or lem matization algorithms to normalize words before counting them. Applying linguistic structure rules to analyze sentences. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
        "references": ""
    },
    {
        "question": ": Microsoft Azure provides the _______ service - a cl oud-based platform for creating, managing, and publ ishing machine learning models.",
        "options": [
            "A. Azure Machine Learning",
            "B. Azure Deep Learning",
            "C. Azure AI Learning",
            "D. Azure Cognitive Learning"
        ],
        "correct": "A. Azure Machine Learning",
        "explanation": "Explanation Microsoft Azure provides the Azure Mach ine Learning service - a cloud-based platform for c reating, managing, and publishing machine learning models.",
        "references": ""
    },
    {
        "question": ": A technique that uses mathematics and statistics to  create a model that can predict unknown values. Ch oose the correct option.",
        "options": [
            "A. Hadoop services",
            "B. Deep learning",
            "C. Machine learning",
            "D. Congitive Learning"
        ],
        "correct": "C. Machine learning",
        "explanation": "Explanation Machine learning is a technique that us es mathematics and statistics to create a model tha t can predict unknown values. Reference Link: https://doc s.microsoft.com/en-us/learn/modules/use-automated- machine-learning/what-is-ml",
        "references": ""
    },
    {
        "question": ": You want to use the Speech service to build an appl ication that reads incoming email message subjects aloud. Which API should you use?",
        "options": [
            "A. Language detection",
            "B. Language API",
            "C. Text Language",
            "D. Text-to-Speech"
        ],
        "correct": "D. Text-to-Speech",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": To use the Speech service in an application, you mu st provision an appropriate resource. Choose the co rrect options.",
        "options": [
            "A. Speech recognition resource",
            "B. A Cognitive Services resource",
            "C. Speech synthesis resource",
            "D. A Speech resource"
        ],
        "correct": "",
        "explanation": "Explanation To use the Speech service in an applica tion, you must provision an appropriate resource su ch as A Speech resource, A Cognitive Services resource. Ref erence Link: https://docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/2-get- started-azure",
        "references": ""
    },
    {
        "question": ": The Language service is a part of the Azure Cogniti ve Services offerings that can perform advanced ____________ over raw text.",
        "options": [
            "A. Language identification",
            "B. Text Extraction",
            "C. Computer Vision service",
            "D. Natural language processing"
        ],
        "correct": "D. Natural language processing",
        "explanation": "Explanation The Language service is a part of the A zure Cognitive Services offerings that can perform advanced natural language processing over raw text. Referenc e Link: https://docs.microsoft.com/en- in/learn/modules/analyze-text-with-text-analytics-s ervice/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": What are the compute resource you can create in Azu re ML Studio? Choose the correct options.",
        "options": [
            "A. Interface Clusters",
            "B. Compute Clusters",
            "C. Attached Cluster",
            "D. Compute Instances"
        ],
        "correct": "",
        "explanation": "Explanation There are four kinds of compute resourc e you can create: Compute Instances, Attached Compu te, Compute Clusters, Inference Clusters Reference Link : https://docs.microsoft.com/en-us/learn/modules/us e- automated-machine-learning/create-compute",
        "references": ""
    },
    {
        "question": ": Whether a person is suffering from a particular dis ease or not can be termed as a ______________.",
        "options": [
            "A. clustering",
            "B. classification",
            "C. regression",
            "D. All of the above"
        ],
        "correct": "B. classification",
        "explanation": "Explanation Whether a person is suffering from a di sease or Not can be termed as a classification prob lem.",
        "references": ""
    },
    {
        "question": ": What all details are required for creating a new Ma chine Learning resource? Choose the correct options .",
        "options": [
            "A. Resource group",
            "B. Password vault",
            "C. Subscription",
            "D. Key vault"
        ],
        "correct": "",
        "explanation": "Explanation Subscription, Resource group, Key vault  are required for creating a new Machine Learning resource. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/use-automated-machine-learning/create- workspace",
        "references": ""
    },
    {
        "question": ": What is the foundation for most AI solutions?",
        "options": [
            "A. Deep Learning",
            "B. All of the above",
            "C. Data Analysis",
            "D. Machine Learning"
        ],
        "correct": "D. Machine Learning",
        "explanation": "Explanation Machine Learning is the foundation for most AI solutions",
        "references": ""
    },
    {
        "question": ": Your Azure subscription will never be charged any a mount for data storage as long as the Azure Machine Learning workspace exists in your subscription",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation Your Azure subscription will be charged  a small amount for data storage as long as the Azu re Machine Learning workspace exists in your subscript ion. Reference Link: https://docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/cre ate-workspace",
        "references": ""
    },
    {
        "question": ": The free tier edition of Read API allows for _ page s, versus __ for the paid version",
        "options": [
            "A. 21000",
            "B. 20000",
            "C. 22,000",
            "D. 23000",
            "A. This application detects damage in your windshiel d. If the application detects a defect, have the",
            "B. This application detects damage in any glass surf ace, but you must accept responsibility for using i t",
            "C. When used in good lighting conditions, this appli cation can be used to identify potentially dangerou s",
            "D. All of the above"
        ],
        "correct": "C. When used in good lighting conditions, this appli cation can be used to identify potentially dangerou s",
        "explanation": "Explanation You should be transparent about the lim itations of the application. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": Which programming languages are supported in Azure machine learning Designer?",
        "options": [
            "A. C#",
            "B. R",
            "C. Scala",
            "D. Python"
        ],
        "correct": "D. Python",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": A graphical interface enabling no-code development of machine learning solutions. Choose the correct o ption.",
        "options": [
            "A. Azure Machine Learning designer",
            "B. Automated machine learning",
            "C. ML Studio",
            "D. Machine Learning Dashboard"
        ],
        "correct": "A. Azure Machine Learning designer",
        "explanation": "Explanation Azure Machine Learning designer is a gr aphical interface enabling no-code development of machine learning solutions.",
        "references": ""
    },
    {
        "question": ": Which Azure service is best for detecting popular b rand logos?",
        "options": [
            "A. Computer Vision",
            "B. Object Detection",
            "C. Azure Portal",
            "D. Custom Vision"
        ],
        "correct": "A. Computer Vision",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Identify people or objects, such as cars, in a spac e and map their movement within that space. Choose the correct option.",
        "options": [
            "A. Non-Spatial Analysis",
            "B. None of the above",
            "C. Temporal Analysis",
            "D. Spatial Analysis"
        ],
        "correct": "D. Spatial Analysis",
        "explanation": "Explanation Spatial Analysis: Identify people or ob jects, such as cars, in a space and map their movem ent within that space. Reference Link: https://docs.microsoft. com/en-us/learn/modules/analyze-images-computer- vision/1-introduction",
        "references": ""
    },
    {
        "question": ": An image is an array of pixel values which can be u sed as _________ to train machine learning models t hat make predictions about the image and its contents.",
        "options": [
            "A. Entities",
            "B. Objects",
            "C. Hyperparameters",
            "D. Features"
        ],
        "correct": "D. Features",
        "explanation": "Explanation An image is just an array of pixel valu es. These numeric values can be used as features to  train machine learning models that make predictions about  the image and its contents. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/1-introduction",
        "references": ""
    },
    {
        "question": ": Bots typically manage conversation flows using a co mbination of _________ and ____________ responses that guide the user to a resolution.",
        "options": [
            "A. Restricted option",
            "B. English language",
            "C. Constrained option",
            "D. Natural language"
        ],
        "correct": "",
        "explanation": "Explanation Regardless of the channel used, bots ty pically manage conversation flows using a combinati on of natural language and constrained option responses t hat guide the user to a resolution. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
        "references": ""
    },
    {
        "question": ": The free tier edition of Read API allows for____ pa ges, versus ____for the paid version",
        "options": [
            "A. 2-2,000",
            "B. 2-10,000",
            "C. 20 -Unlimited",
            "D. 20-30,000"
        ],
        "correct": "A. 2-2,000",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": If you create a Cognitive Services resource, client  applications need different keys and endpoint for different service they use.",
        "options": [
            "A. FALSE",
            "B. TRUE",
            "A. Casual",
            "B. Conversational",
            "C. Transactional",
            "D. Chatty"
        ],
        "correct": "B. Conversational",
        "explanation": "Explanation Bots are designed to interact with user s in a conversational manner. Reference Link: https://docs.microsoft.com/en-in/learn/modules/buil d-faq-chatbot-qna-maker-azure-bot-service/1-introdu ction/",
        "references": ""
    },
    {
        "question": ": You can submit only single document at a time for a nalysis.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation You can submit multiple documents at a time for analysis. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": Some potential uses for computer vision include fol lowing aspects. Choose the correct option.",
        "options": [
            "A. Spatial Analysis",
            "B. Text Extraction",
            "C. Content creation",
            "D. Content Organization"
        ],
        "correct": "",
        "explanation": "Explanation Some potential uses for computer vision  include: Content Organization, Text Extraction, Sp atial Analysis. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/analyze-images-computer-visio n/1- introduction",
        "references": ""
    },
    {
        "question": ":Which feature enables non-experts to quickly create  an effective machine learning model from data?",
        "options": [
            "A. ML Studio",
            "B. Automated machine learning",
            "C. Machine Learning Dashboard",
            "D. Azure Machine Learning designer"
        ],
        "correct": "B. Automated machine learning",
        "explanation": "Explanation Automated machine learning feature enab les non-experts to quickly create an effective mach ine learning model from data.",
        "references": ""
    },
    {
        "question": ": AI algorithms that detect, recognize, and analyze h uman faces in images. Choose the correct option.",
        "options": [
            "A. Image analysis",
            "B. Object Detection",
            "C. All of the above",
            "D. Face service"
        ],
        "correct": "D. Face service",
        "explanation": "Explanation The Azure Face service provides AI algo rithms that detect, recognize, and analyze human fa ces in images. Reference Link: https://docs.microsoft.com/ en-us/azure/cognitive-services/face/overview",
        "references": ""
    },
    {
        "question": ": Azure Machine Learning provides the following featu res. Choose the correct option.",
        "options": [
            "A. Automated machine learning",
            "B. Azure Machine Learning designer",
            "C. Analytical Machine Learning",
            "D. Data and compute management"
        ],
        "correct": "",
        "explanation": "Explanation Azure Machine Learning provides the fol lowing features and capabilities:Automated machine learning, Azure Machine Learning designer, Data and  compute management, Pipelines",
        "references": ""
    },
    {
        "question": ": Which compute resources are deployment targets for predictive services that use your trained model? A. Compute Instances",
        "options": [
            "B. Inference Clusters",
            "C. Compute Clusters",
            "D. Attached Compute"
        ],
        "correct": "B. Inference Clusters",
        "explanation": "Explanation Inference Clusters: Deployment targets for predictive services that use your trained model s. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/use-automated-machine-learning/create- compute",
        "references": ""
    },
    {
        "question": ": Which intent is a required intent and can't be dele ted or renamed?",
        "options": [
            "A. None intent",
            "B. TurnOff intent",
            "C. TurnOn intent",
            "D. Greeting intent"
        ],
        "correct": "A. None intent",
        "explanation": "Explanation In a Language Understanding application , the None intent is created but left empty on purp ose. The None intent is a required intent and can't be delet ed or renamed. Fill it with utterances that are out side of your domain. Reference Link: https://docs.microsoft.com/ en-in/learn/modules/recognize-synthesize-speech/2-g et- started-azure",
        "references": ""
    },
    {
        "question": ": To use Azure Machine Learning, you create _________ __ in your Azure subscription. Choose the correct option.",
        "options": [
            "A. a workarea",
            "B. a workground",
            "C. a playground",
            "D. a workspace",
            "A. Create an empty knowledge base, and then manually  copy and paste the FAQ entries into it.",
            "B. Import a pre-defined chit-chat data source.",
            "C. Import the existing FAQ document into a new knowl edge base.",
            "D. None of the above"
        ],
        "correct": "C. Import the existing FAQ document into a new knowl edge base.",
        "explanation": "Explanation You can import question and answer pair s from an existing FAQ document into a QnA Maker knowledge base. Reference Link: https://docs.micros oft.com/en-in/learn/modules/build-faq-chatbot-qna-m aker- azure-bot-service/1-introduction/",
        "references": ""
    },
    {
        "question": ": What is used to to orchestrate model training, depl oyment, and management tasks?",
        "options": [
            "A. Python script",
            "B. Pipelines",
            "C. Notebooks",
            "D. Bash Script"
        ],
        "correct": "B. Pipelines",
        "explanation": "Explanation Data scientists, software engineers, an d IT operations professionals can define pipelines to orchestrate model training, deployment, and managem ent tasks.",
        "references": ""
    },
    {
        "question": ": User can use the workspace to manage data, ________ _, code, __________, and other artifacts related to your machine learning workloads. Choose the correct opti on.",
        "options": [
            "A. generic resources",
            "B. logs",
            "C. models",
            "D. compute resources"
        ],
        "correct": "",
        "explanation": "Explanation Explanation User can use this workspace to manage d ata, compute resources, code, models, and other artifacts related to your machine learning workloads. Referen ce Link: https://docs.microsoft.com/en- us/learn/modules/use-automated-machine-learning/cre ate-workspace",
        "references": ""
    },
    {
        "question": ": An area of artificial intelligence (AI) in which so ftware systems are designed to perceive the world v isually, though cameras, images, and video. Choose the corre ct option.",
        "options": [
            "A. NLP",
            "B. Computer Vision",
            "C. Machine vision",
            "D. Image processing"
        ],
        "correct": "B. Computer Vision",
        "explanation": "Explanation Computer vision is an area of artificia l intelligence (AI) in which software systems are d esigned to perceive the world visually, though cameras, images , and video. Reference Link: https://docs.microsoft .com/en- us/learn/paths/explore-computer-vision-microsoft-az ure/",
        "references": ""
    },
    {
        "question": ": Which service can help to Identify and categorize e ntities in the text?",
        "options": [
            "A. Language API service",
            "B. Text Language service",
            "C. Language cognitive service",
            "D. Text analytics service"
        ],
        "correct": "C. Language cognitive service",
        "explanation": "Explanation Language cognitive service can help ide ntify and categorize entities in the text. Referenc e Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
        "references": ""
    },
    {
        "question": ": Which compute resources are development workstation s that data scientists can use to work with data an d models?",
        "options": [
            "A. Attached Compute",
            "B. Compute Instances",
            "C. Inference Clusters",
            "D. Compute Clusters"
        ],
        "correct": "B. Compute Instances",
        "explanation": "Explanation Compute Instances: Development workstat ions that data scientists can use to work with data  and models. Reference Link: https://docs.microsoft.com/ en-us/learn/modules/use-automated-machine- learning/create-compute",
        "references": ""
    },
    {
        "question": ": How does the translation engine know when an uttera nce has finished?",
        "options": [
            "A. After a pause in the audio",
            "B. User presses the spacebar",
            "C. User needs to speak the word `Stop'.",
            "D. After 10 words have been spoken."
        ],
        "correct": "A. After a pause in the audio",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": What is AI?",
        "options": [
            "A. All of the above",
            "B. It is used to automatically detect errors or unus ual activity in a system",
            "C. Software that imitates human behaviors and capabi lities",
            "D. It has machine learning technology to make predic tion and draw conclusions from data."
        ],
        "correct": "A. All of the above",
        "explanation": "Explanation AI is the creation of software that imi tates human behaviors and capabilities. Key element s include: Machine learning - This is often the foundation for  an AI system, and is the way we \"teach\" a computer  model to make prediction and draw conclusions from data. Ano maly detection - The capability to automatically de tect errors or unusual activity in a system. Computer vi sion - The capability of software to interpret the world visually through cameras, video, and images. Natural languag e processing - The capability for a computer to int erpret written or spoken language, and respond in kind. Co nversational AI - The capability of a software \"age nt\" to participate in a conversation.",
        "references": ""
    },
    {
        "question": ": Which service provides an application programming i nterface (API) that developers can use to create an omaly detection solutions?",
        "options": [
            "A. Binary classification",
            "B. Regression",
            "C. None of the above",
            "D. Anomaly Detector Correct Answer: D"
        ],
        "correct": "",
        "explanation": "Explanation In Microsoft Azure, the Anomaly Detecto r service provides an application programming inter face (API) that developers can use to create anomaly det ection solutions.",
        "references": ""
    },
    {
        "question": ": Cloud-based resources on which you can run model tr aining and data exploration processes. Choose the correct option.",
        "options": [
            "A. Resource targets",
            "B. Artifacts",
            "C. Storage targets",
            "D. Compute targets"
        ],
        "correct": "D. Compute targets",
        "explanation": "Explanation Compute targets are cloud-based resourc es on which you can run model training and data exploration processes. Reference Link: https://docs .microsoft.com/en-us/learn/modules/use-automated- machine-learning/create-compute",
        "references": ""
    },
    {
        "question": ": Encoding words or terms as numeric features that ca n be used to train a machine learning model.",
        "options": [
            "A. FALSE",
            "B. TRUE"
        ],
        "correct": "B. TRUE",
        "explanation": "Explanation Encoding words or terms as numeric feat ures that can be used to train a machine learning m odel. For example, to classify a text document based on t he terms it contains. This technique is often used to perform sentiment analysis, in which a document is classifi ed as positive or negative. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
        "references": ""
    },
    {
        "question": ": What information is required to connect to your dep loyed service from a client application? Choose the correct option.",
        "options": [
            "A. Access Key for your service",
            "B. REST endpoint for your service",
            "C. Primary Key for your service",
            "D. Endpoint URL Correct Answer: BC"
        ],
        "correct": "",
        "explanation": "Explanation You need below information to connect t o your deployed service from a client application. The REST endpoint for your service the Primary Key for your service Reference Link: https://docs.microsoft.com/ en- us/learn/modules/use-automated-machine-learning/dep loy-model",
        "references": ""
    },
    {
        "question": ": What compute resources are based on standard Azure virtual machine images?Choose the correct option.",
        "options": [
            "A. Interface Clusters",
            "B. Attached Cluster",
            "C. Compute Clusters",
            "D. Compute Instances"
        ],
        "correct": "",
        "explanation": "Explanation Compute instances and clusters are base d on standard Azure virtual machine images. Referen ce Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/create-compute",
        "references": ""
    },
    {
        "question": ": Which service provides an interface to the knowledg e base through one or more channels?",
        "options": [
            "A. A bot resource",
            "B. A historical data",
            "C. A knowledge base",
            "D. A bot service"
        ],
        "correct": "D. A bot service",
        "explanation": "Explanation A bot service that provides an interfac e to the knowledge base through one or more channel s. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/build-faq-chatbot-qna-maker-azure-bot- service/1-introduction/",
        "references": ""
    },
    {
        "question": ": In Azure Machine Learning, data for model training and other operations is usually encapsulated in an object called a __________.",
        "options": [
            "A. All of the above",
            "B. dataset C. file",
            "D. Database"
        ],
        "correct": "B. dataset C. file",
        "explanation": "Explanation In Azure Machine Learning, data for mod el training and other operations is usually encapsu lated in an object called a dataset. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/use-automat ed- machine-learning/data",
        "references": ""
    },
    {
        "question": ": The Computer Vision service can use _______________  capabilities to detect printed and handwritten tex t in images.",
        "options": [
            "A. Intelligent character recognition (ICR)",
            "B. Optical character recognition (OCR)",
            "C. Optical mark recognition (OMR)",
            "D. None of the above"
        ],
        "correct": "B. Optical character recognition (OCR)",
        "explanation": "Explanation The Computer Vision service can use opt ical character recognition (OCR) capabilities to de tect printed and handwritten text in images. Reference L ink: https://docs.microsoft.com/en- us/learn/modules/analyze-images-computer-vision/2-i mage-analysis-azure",
        "references": ""
    },
    {
        "question": ": Which classification involves training a machine le arning model to classify images based on their contents?",
        "options": [
            "A. Semantic segmentation",
            "B. Image classification",
            "C. Image analysis",
            "D. Object detection"
        ],
        "correct": "B. Image classification",
        "explanation": "Explanation Image classification involves training a machine learning model to classify images based o n their contents. Reference Link: https://docs.microsoft.co m/en-us/learn/modules/get-started-ai-fundamentals/4 - understand-computer-vision",
        "references": ""
    },
    {
        "question": ": In automated ML, which vitual machine image is reco mmended to achieve the optimal balance of cost and performance? A. Standard_DS11_v2",
        "options": [
            "B. None of the above",
            "C. Standard_D15_v2",
            "D. Standard_DS13_v2"
        ],
        "correct": "",
        "explanation": "Explanation In automated ML, the Standard_DS11_v2 i mage is recommended to achieve the optimal balance of cost and performance. Reference Link: https://docs. microsoft.com/en-us/learn/modules/use-automated- machine-learning/create-compute",
        "references": ""
    },
    {
        "question": ": To implement the Bot solution, you need the followi ng components. Choose the correct answer.",
        "options": [
            "A. A bot service",
            "B. A knowledge base",
            "C. A historical data",
            "D. A bot resource"
        ],
        "correct": "",
        "explanation": "Explanation To implement BOT solution, you need: A knowledge base of question and answer pairs - usual ly with some built-in natural language processing model to enable questions that can be phrased in multiple wa ys to be understood with the same semantic meaning. A bot se rvice that provides an interface to the knowledge b ase through one or more channels. Reference Link: https ://docs.microsoft.com/en-in/learn/modules/build-faq - chatbot-qna-maker-azure-bot-service/1-introduction/",
        "references": ""
    },
    {
        "question": ": You plan to build an application that uses the Spee ch service to transcribe audio recordings of phone calls into text, and then submits the transcribed text to  the Text Analytics service to extract key phrases.  You want to manage access and billing for the applicati on services in a single Azure resource. Which type of Azure resource should you create?",
        "options": [
            "A. Cognitive Services",
            "B. Computer Vision",
            "C. None of the above",
            "D. Custom Vision",
            "A. Seeing Vision",
            "B. Seeing ML",
            "C. Seeing Algo",
            "D. Seeing AI"
        ],
        "correct": "D. Seeing AI",
        "explanation": "Explanation The Seeing AI app is a great example of  the power of computer vision. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": When categorizing an image, the Computer Vision ser vice supports two specialized domain models. Choose the correct option.",
        "options": [
            "A. People",
            "B. Celebrities",
            "C. Areas",
            "D. Landmarks"
        ],
        "correct": "",
        "explanation": "Explanation When categorizing an image, the Compute r Vision service supports two specialized domain models: Celebrities, Landmarks Reference Link: https://docs .microsoft.com/en-us/learn/modules/analyze-images- computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": Translator text supports languages.",
        "options": [
            "A. more than 60",
            "B. up to 10",
            "C. up to 50",
            "D. up to 30",
            "A. Gearnal Data",
            "B. Advance Data",
            "C. Complex Data",
            "D. Normalize Data"
        ],
        "correct": "D. Normalize Data",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You are developing an application or tourists to us e as a text-based or audio-based translator. Which Azure services can help?",
        "options": [
            "A. Text Analytics",
            "B. Text Translate",
            "C. Translator Text",
            "D. Azure Speech"
        ],
        "correct": "C. Translator Text",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": To use the Language service in an application, you can choose to provision either of the following typ es of resource. Choose the correct options.",
        "options": [
            "A. A Cognitive Services API calls",
            "B. A Cognitive Services resource",
            "C. A Language resource",
            "D. A Language Identifier API service"
        ],
        "correct": "",
        "explanation": "Explanation To use the Language service in an appli cation, you must provision an appropriate resource in your Azure subscription. You can choose to provision eit her of the following types of resource: A Language resource, ACognitive Services resource Reference Link: https:/ /docs.microsoft.com/en-in/learn/modules/analyze-tex t-with- text-analytics-service/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": Which compute resources links to existing Azure com pute resources, such as Virtual Machines or Azure Databricks clusters?",
        "options": [
            "A. Attached Compute",
            "B. Kubernetes Clusters",
            "C. Compute Clusters",
            "D. Inference Clusters"
        ],
        "correct": "A. Attached Compute",
        "explanation": "Explanation Attached Compute: Links to existing Azu re compute resources, such as Virtual Machines or A zure Databricks clusters. Reference Link: https://docs.m icrosoft.com/en-us/learn/modules/use-automated-mach ine- learning/create-compute",
        "references": ""
    },
    {
        "question": ": Which service help to perform sentiment analysis on  text to determine a positive or negative sentiment ?",
        "options": [
            "A. Language cognitive service",
            "B. Language API service",
            "C. Text analytics service",
            "D. Text Language service"
        ],
        "correct": "A. Language cognitive service",
        "explanation": "Explanation Language cognitive service can help to perform sentiment analysis on text to determine a p ositive or negative sentiment. Reference Link: https://docs.mi crosoft.com/en-in/learn/modules/analyze-text-with-t ext- analytics-service/1-introduction",
        "references": ""
    },
    {
        "question": ": What provides first-line of automated support throu gh the full range of channels that we use to communicate?",
        "options": [
            "A. Robots service",
            "B. Bots service",
            "C. LUIS service",
            "D. QnA Maker"
        ],
        "correct": "B. Bots service",
        "explanation": "Explanation Bots are used to provide a first-line o f automated support through the full range of chann els that we use to communicate.",
        "references": ""
    },
    {
        "question": ": Using the pre-built machine learning classification  model, the service evaluates the text and returns a sentiment score in the range of _________.",
        "options": [
            "A. 0 to 1",
            "B. 0 to 100",
            "C. 0 to 1.5",
            "D. 0 to 10"
        ],
        "correct": "A. 0 to 1",
        "explanation": "Explanation Using the pre-built machine learning cl assification model, the service evaluates the text and returns a sentiment score in the range of 0 to 1. Reference L ink: https://docs.microsoft.com/en-in/learn/modules /analyze- text-with-text-analytics-service/2-get-started-azur e",
        "references": ""
    },
    {
        "question": ": In Azure Machine Learning, operations that you run are called ___________.",
        "options": [
            "A. experiments",
            "B. jobs",
            "C. runs",
            "D. None of the above"
        ],
        "correct": "A. experiments",
        "explanation": "Explanation In Azure Machine Learning, operations t hat you run are called experiments. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
        "references": ""
    },
    {
        "question": ": You are using the Form Recognizer service to analyz e receipts that you have scanned into JPG format images. What is the maximum file size of JPG file y ou can submit to the pre-built receipt model?",
        "options": [
            "A. 100MB",
            "B. 10MB",
            "C. 20MB",
            "D. 50MB"
        ],
        "correct": "",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The confidence score may be greater than 1 as a res ult of the mixed language text.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "B. FALSE",
        "explanation": "Explanation The confidence score may be less than 1  as a result of the mixed language text. Reference Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": Which service provides a dedicated QnA Maker portal  web-based interface that you can use to create, train, publish, and manage knowledge bases?",
        "options": [
            "A. Bots service",
            "B. LUIS service",
            "C. Robots service",
            "D. QnA Maker"
        ],
        "correct": "D. QnA Maker",
        "explanation": "Explanation The QnA Maker service provides a dedica ted QnA Maker portal web-based interface that you c an use to create, train, publish, and manage knowledge bas es. Reference Link: https://docs.microsoft.com/en- in/learn/modules/build-faq-chatbot-qna-maker-azure- bot-service/2-get-started-qna-bot",
        "references": ""
    },
    {
        "question": ": An advanced machine learning technique in which ind ividual pixels in the image are classified accordin g to the object to which they belong.",
        "options": [
            "A. Image classification",
            "B. Object detection",
            "C. Image analysis",
            "D. Semantic segmentation"
        ],
        "correct": "D. Semantic segmentation",
        "explanation": "Explanation Semantic segmentation is an advanced ma chine learning technique in which individual pixels  in the image are classified according to the object to whi ch they belong. Reference Link: https://docs.micros oft.com/ en- us/learn/modules/get-started-ai-fundamentals/4-unde rstand-computer-vision",
        "references": ""
    },
    {
        "question": ": Language cognitive service can help simplify applic ation development by using pre-trained models that can do the following, choose the correct options.",
        "options": [
            "A. Perform sentiment analysis on text",
            "B. None of the above",
            "C. Identify and categorize entities in the text.",
            "D. Determine the language of a document or text"
        ],
        "correct": "",
        "explanation": "Explanation In Microsoft Azure, the Language cognit ive service can help simplify application developme nt by using pre-trained models that can: Determine the la nguage of a document or text (for example, French o r English). Perform sentiment analysis on text to det ermine a positive or negative sentiment. Extract ke y phrases from text that might indicate its main talking poin ts. Identify and categorize entities in the text. E ntities can be people, places, organizations, or even everyday ite ms such as dates, times, quantities, and so on. Ref erence Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/1-introduction",
        "references": ""
    },
    {
        "question": ": A machine learning based technique that analyzes da ta over time and identifies unusual changes. Choose the correct option.",
        "options": [
            "A. Outlier detection",
            "B. Intrusion detection",
            "C. Anomaly detection",
            "D. Novelty detection"
        ],
        "correct": "C. Anomaly detection",
        "explanation": "Explanation By using anomaly detection - a machine learning based technique that analyzes data over ti me and identifies unusual changes. Reference Link: https:/ /docs.microsoft.com/en-us/learn/modules/get-started -ai- fundamentals/3-understand-anomaly-detection",
        "references": ""
    },
    {
        "question": ": What is one aspect that may impair facial detection ?",
        "options": [
            "A. Medium angles",
            "B. Small angles C. Angles",
            "D. Extreme angles"
        ],
        "correct": "D. Extreme angles",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": The Text-to-Speech Neural voices leverage Neural ne tworks resulting in a more robotic-sounding voice.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": A sentiment score with values closer to 1 being a _ _________ sentiment.",
        "options": [
            "A. Positive",
            "B. All of the above",
            "C. Negative",
            "D. Neutral"
        ],
        "correct": "A. Positive",
        "explanation": "Explanation Language service evaluates the text and  returns a sentiment score in the range of 0 to 1, with values closer to 1 being a positive sentiment. Reference L ink: https://docs.microsoft.com/en-in/learn/modules /analyze- text-with-text-analytics-service/2-get-started-azur e",
        "references": ""
    },
    {
        "question": ": Most computer vision solutions are based on machine  learning models that can be applied to _______ fro m cameras, videos, or images.",
        "options": [
            "A. Raw input",
            "B. Visual input",
            "C. Text input",
            "D. Object input"
        ],
        "correct": "B. Visual input",
        "explanation": "Explanation Most computer vision solutions are base d on machine learning models that can be applied to  visual input from cameras, videos, or images. Reference Li nk: https://docs.microsoft.com/en-us/learn/modules/ get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": Sensors in the car collect _________, such as engin e revolutions, brake temperature, and so on.",
        "options": [
            "A. Telemetry",
            "B. Logs",
            "C. Objects",
            "D. Metrics"
        ],
        "correct": "A. Telemetry",
        "explanation": "Explanation Sensors in the car collect telemetry, s uch as engine revolutions, brake temperature, and s o on. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/get-started-ai-fundamentals/3-understan d- anomaly-detection",
        "references": ""
    },
    {
        "question": ": The language detection service will focus on the __ __________ in the text.",
        "options": [
            "A. Expressive language",
            "B. Dominant language",
            "C. Predominant language",
            "D. All of the above"
        ],
        "correct": "C. Predominant language",
        "explanation": "Explanation The language detection service will foc us on the predominant language in the text. Referen ce Link: https://docs.microsoft.com/en-in/learn/modules/anal yze-text-with-text-analytics-service/2-get-started- azure",
        "references": ""
    },
    {
        "question": ": This causes Azure Machine Learning to automatically  preprocess the features before training in Automated ML. Choose the correct option.",
        "options": [
            "A. Enable Primary metric",
            "B. All of the above",
            "C. Activate featurization",
            "D. Enable featurization"
        ],
        "correct": "",
        "explanation": "Explanation In Featurization settings. Enable featu rization must be Selected which causes Azure Machin e Learning to automatically preprocess the features before tra ining. Reference Link: https://docs.microsoft.com/e n- us/learn/modules/use-automated-machine-learning/dat a",
        "references": ""
    },
    {
        "question": ": You are using Azure Machine Learning designer to cr eate a training pipeline for a binary classificatio n model. You have added a dataset containing features  and labels, a Two-Class Decision Forest module, an d a Train Model module. You plan to use Score Model a nd Evaluate Model modules to test the trained model with a subset of the dataset that was not use d for training. Which additional kind of module sho uld you add?",
        "options": [
            "A. Update Data",
            "B. Split Data",
            "C. Add Data",
            "D. Remove Data"
        ],
        "correct": "B. Split Data",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": Speech cognitive service, which includes the follow ing application programming interfaces (APIs). Choo se the correct options.",
        "options": [
            "A. The Text-to-Text API",
            "B. The Text-to-Speech API",
            "C. All of the above",
            "D. The Speech-to-Text API"
        ],
        "correct": "",
        "explanation": "Explanation The Speech cognitive service, which inc ludes the following application programming interfa ces (APIs): The Speech-to-Text API The Text-to-Speech A PI Reference Link: https://docs.microsoft.com/en- in/learn/modules/recognize-synthesize-speech/2-get- started-azure",
        "references": ""
    },
    {
        "question": ": You want to use the Computer Vision service to anal yze images of locations and identify well-known buildings. What should you do?",
        "options": [
            "A. Retrieve the objects in the image.",
            "B. Retrieve the categories for the image, specifying t he landmarks domain C. None of the above",
            "D. Retrieve the categories for the image, specifying  the celebrities domain"
        ],
        "correct": "B. Retrieve the categories for the image, specifying t he landmarks domain C. None of the above",
        "explanation": "Explanation The landmarks domain includes many well -known buildings around the world. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": The text analytics capability is useful for detecti ng positive and negative sentiment in below areas. Choose the correct options",
        "options": [
            "A. Customer reviews",
            "B. Social media",
            "C. Discussion forums",
            "D. All of the above"
        ],
        "correct": "D. All of the above",
        "explanation": "Explanation The text analytics capabilities in the Language service can evaluate text and return senti ment scores and labels for each sentence. This capability is us eful for detecting positive and negative sentiment in social media, customer reviews, discussion forums and more . Reference Link: https://docs.microsoft.com/en- in/learn/modules/analyze-text-with-text-analytics-s ervice/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": Seeing AI app harnesses the power of AI to open up the visual world and describe nearby _______, ___________and __________.",
        "options": [
            "A. Text",
            "B. People",
            "C. None of the above",
            "D. Object"
        ],
        "correct": "",
        "explanation": "Explanation The Seeing AI app is a great example of  the power of computer vision. Designed for the bli nd and low vision community, the Seeing AI app harnesses t he power of AI to open up the visual world and desc ribe nearby people, text and objects. Reference Link: ht tps://docs.microsoft.com/en-us/learn/modules/get-st arted-ai- fundamentals/4-understand-computer-vision",
        "references": ""
    },
    {
        "question": ":Which machine learning model is suitable for predic ting categories or classes?",
        "options": [
            "A. Regression",
            "B. Clustering",
            "C. Time series forecasting",
            "D. Classification"
        ],
        "correct": "D. Classification",
        "explanation": "Explanation Classification is used for predicting c ategories or classes. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
        "references": ""
    },
    {
        "question": ": Machine learning models must be trained with live d ata.",
        "options": [
            "A. FALSE",
            "B. TRUE"
        ],
        "correct": "A. FALSE",
        "explanation": "Explanation Machine learning models must be trained  with existing data. Reference Link: https://docs.microsoft.com/en-us/learn/modules/use- automated-machine-learning/data",
        "references": ""
    },
    {
        "question": ": Which of the following tasks would be a good fit fo r the Speech-to-Text?",
        "options": [
            "A. Real-time voice-chat transcription from a microph one",
            "B. Creating an audio file from a famous quote",
            "C. None of the above",
            "D. Translating a document written in English into Ge rman."
        ],
        "correct": "A. Real-time voice-chat transcription from a microph one",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": In Azure Machine Learning, you can deploy a service  as an __________ or to an __________________ cluster.",
        "options": [
            "A. Azure Inference Service (AIS) cluster.",
            "B. Azure Container Instances (ACI)",
            "C. Azure Compute Instances (ACI) D. Azure Kubernetes Service (AKS) cluster."
        ],
        "correct": "",
        "explanation": "Explanation In Azure Machine Learning, you can depl oy a service as an Azure Container Instances (ACI) or to an Azure Kubernetes Service (AKS) cluster. Reference L ink: https://docs.microsoft.com/en-us/learn/modules /use- automated-machine-learning/data",
        "references": ""
    },
    {
        "question": ": Which option in Automated ML can calculate feature importance for the best model? Choose the correct option.",
        "options": [
            "A. Primary metric",
            "B. Explain best model",
            "C. Blocked algorithms",
            "D. Get best model"
        ],
        "correct": "B. Explain best model",
        "explanation": "Explanation Explain best model: Selected - this opt ion causes automated machine learning to calculate feature importance for the best model; making it possible t o determine the influence of each feature on the pr edicted label. Reference Link: https://docs.microsoft.com/e n-us/learn/modules/use-automated-machine-learning/d ata",
        "references": ""
    },
    {
        "question": ": Image is an array of pixel values which can be used  as _________ to train machine learning models that make predictions about the image and its contents.",
        "options": [
            "A. Objects",
            "B. Entities",
            "C. Hyperparameters",
            "D. Features"
        ],
        "correct": "D. Features",
        "explanation": "Explanation An image is just an array of pixel valu es. These numeric values can be used as features to  train machine learning models that make predictions about  the image and its contents. Reference Link: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/1-introduction",
        "references": ""
    },
    {
        "question": ": The Computer vision service includes a model that h as been trained to identify thousands of well-known celebrities from the worlds of sports, entertainmen t, and business. A. FALSE",
        "options": [
            "B. TRUE"
        ],
        "correct": "B. TRUE",
        "explanation": "Explanation Celebrities - The service includes a mo del that has been trained to identify thousands of well- known celebrities from the worlds of sports, entertainmen t, and business. Reference Link: https://docs.micro soft.com/ en- us/learn/modules/analyze-images-computer-vision/2-i mage-analysis-azure",
        "references": ""
    },
    {
        "question": ": How do you access the QnAmaker portal?",
        "options": [
            "A. qnamaker.ai",
            "B. portal.azure.com",
            "C. cognitive service",
            "D. None of the above"
        ],
        "correct": "A. qnamaker.ai",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You can use the __________ capability of the Langua ge service to identify the language in which text i s written.",
        "options": [
            "A. Language Identification",
            "B. None of the above",
            "C. Language detection",
            "D. Language analyzer"
        ],
        "correct": "C. Language detection",
        "explanation": "Explanation You can use the language detection capa bility of the Language service to identify the lang uage in which text is written. Reference Link: https://docs .microsoft.com/en-in/learn/modules/analyze-text-wit h-text- analytics-service/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": What represents the purpose, or goal, expressed in a user's utterance? A. Entities",
        "options": [
            "B. Objects",
            "C. Utterances",
            "D. Intents"
        ],
        "correct": "D. Intents",
        "explanation": "Explanation An intent represents the purpose, or go al, expressed in a user's utterance. Reference Link : https://docs.microsoft.com/en-in/learn/modules/reco gnize-synthesize-speech/2-get-started-azure",
        "references": ""
    },
    {
        "question": ": How does the translation engine know when an uttera nce has finished?",
        "options": [
            "A. User needs to speak the word `Stop'.",
            "B. After 10 words have been spoken.",
            "C. After a pause in the audio",
            "D. User presses the spacebar"
        ],
        "correct": "C. After a pause in the audio",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": You want to use the Computer Vision service to anal yze images. You also want to use the Text Analytics service to analyze text. You want developers to req uire only one key and endpoint to access all of you r services. What kind of resource should you create i n your Azure subscription?",
        "options": [
            "A. None of the above",
            "B. Custom Vision",
            "C. Computer Vision",
            "D. Cognitive Services"
        ],
        "correct": "D. Cognitive Services",
        "explanation": "Explanation A Cognitive Services resource support b oth Computer Vision and Text Analytics. Reference L ink: https://docs.microsoft.com/en-us/learn/modules/anal yze-images-computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": To classify images based on the type of vehicle the y contain, such as taxis, buses, cyclists, and so o n is an example of __________________.",
        "options": [
            "A. Semantic segmentation B. Image classification",
            "C. Image analysis",
            "D. Object detection"
        ],
        "correct": "",
        "explanation": "Explanation In a traffic monitoring solution you mi ght use an image classification model to classify i mages based on the type of vehicle they contain, such as taxis,  buses, cyclists, and so on. Reference Link: https://docs.microsoft.com/en-us/learn/modules/get- started-ai-fundamentals/4-understand-computer-visio n",
        "references": ""
    },
    {
        "question": ": You use the Text Analytics service to perform senti ment analysis on a document, and a score of 0.99 is returned. What does this score indicate about the d ocument sentiment?",
        "options": [
            "A. The document is positive.",
            "B. None of the above",
            "C. The document is negative.",
            "D. All of the above"
        ],
        "correct": "A. The document is positive.",
        "explanation": "Explanation/Reference:",
        "references": ""
    },
    {
        "question": ": To indentify best model, the training process used some of the data to train the model, and applied a technique called __________ to iteratively test the  trained model with data it wasn't trained with and compare the predicted value with the actual known v alue.",
        "options": [
            "A. None of the above",
            "B. inversion",
            "C. cross-validation",
            "D. Validation"
        ],
        "correct": "C. cross-validation",
        "explanation": "Explanation The best model is identified based on t he evaluation metric you specified (Normalized root  mean squared error). To calculate this metric, the train ing process used some of the data to train the mode l, and applied a technique called cross-validation to iter atively test the trained model with data it wasn't trained with and compare the predicted value with the actual kno wn value. Reference Link: https://docs.microsoft.co m/en- us/learn/modules/use-automated-machine-learning/dat a",
        "references": ""
    },
    {
        "question": "Which solution will be used to identify the locatio n of different classes of vehicle in a traffic moni toring?",
        "options": [
            "A. Semantic segmentation",
            "B. Image analysis",
            "C. Image classification",
            "D. Object detection"
        ],
        "correct": "D. Object detection",
        "explanation": "Explanation A traffic monitoring solution might use  object detection to identify the location of diffe rent classes of vehicle. Reference Link: https://docs.microsoft.com /en-us/learn/modules/get-started-ai-fundamentals/4- understand-computer-vision",
        "references": ""
    },
    {
        "question": ": The first challenge in creating a user support bot is to use the ___________ to create a knowledge bas e.",
        "options": [
            "A. A bot service",
            "B. A knowledge base service",
            "C. QnA Maker service",
            "D. A historical data service"
        ],
        "correct": "C. QnA Maker service",
        "explanation": "Explanation The first challenge in creating a user support bot is to use the QnA Maker service to crea te a knowledge base. Reference Link: https://docs.micros oft.com/en-in/learn/modules/build-faq-chatbot-qna-m aker- azure-bot-service/2-get-started-qna-bot",
        "references": ""
    },
    {
        "question": ": Machine learning models are trained to classify ind ividual objects within an image, and identify their location with a bounding box. Choose the correct op tion.",
        "options": [
            "A. Object detection",
            "B. Image analysis",
            "C. Image classification",
            "D. Semantic segmentation",
            "A. Language cognitive resource",
            "B. Language resource",
            "C. Cognitive Services resource",
            "D. Text analytics resource"
        ],
        "correct": "C. Cognitive Services resource",
        "explanation": "Explanation A Cognitive Services resource - choose this resource type if you plan to use the Language service in combination with other cognitive services, and you want to manage access and billing for these service s together. Reference Link: https://docs.microsoft.com/en-in/le arn/modules/analyze-text-with-text-analytics-servic e/2-get- started-azure",
        "references": ""
    },
    {
        "question": ": A sentiment score with values closer to 0 being a _ _________ sentiment.",
        "options": [
            "A. Neutral",
            "B. Indeterminant",
            "C. Negative",
            "D. Positive"
        ],
        "correct": "C. Negative",
        "explanation": "Explanation Language service evaluates the text and  returns a sentiment score in the range of 0 to 1, with values closer to 0 being a negative sentiment. Reference L ink: https://docs.microsoft.com/en-in/learn/modules / analyze- text-with-text-analytics-service/2-get-started-azur e",
        "references": ""
    },
    {
        "question": ": Normalized root mean squared error metric is a part  of _______________.",
        "options": [
            "A. Time series forecasting",
            "B. Regression",
            "C. Clustering",
            "D. Classification"
        ],
        "correct": "B. Regression",
        "explanation": "Explanation Normalized root mean squared error metr ic is a part of Regression.",
        "references": ""
    },
    {
        "question": ": Some built-in natural language processing model to enable questions that can be phrased in multiple ways to be understood with the same semantic meanin g. Choose the correct term.",
        "options": [
            "A. A bot resource",
            "B. A bot service",
            "C. A historical data",
            "D. A knowledge base"
        ],
        "correct": "D. A knowledge base",
        "explanation": "Explanation A knowledge base of question and answer  pairs - usually with some built-in natural languag e processing model to enable questions that can be ph rased in multiple ways to be understood with the sa me semantic meaning. Reference Link: https://docs.micr osoft.com/en-in/learn/modules/build-faq-chatbot-qna - maker-azure-bot-service/1-introduction/",
        "references": ""
    },
    {
        "question": ": The difference between the predicted and actual val ue known as __________ in the model.",
        "options": [
            "A. prediction",
            "B. Precision",
            "C. error",
            "D. Accuracy"
        ],
        "correct": "C. error",
        "explanation": "Explanation The difference between the predicted an d actual value (known as the residuals) indicates t he amount of error in the model. Reference Link: https://docs .microsoft.com/en-us/learn/modules/use-automated-ma chine- learning/data",
        "references": ""
    },
    {
        "question": ": The Computer Vision service can identify famous lan dmarks, such as the Taj Mahal and the Statue of Liberty.",
        "options": [
            "A. TRUE",
            "B. FALSE"
        ],
        "correct": "A. TRUE",
        "explanation": "Explanation Landmarks - The Computer Vision service  can identify famous landmarks, such as the Taj Mah al and the Statue of Liberty. Reference Link: https://docs .microsoft.com/en-us/learn/modules/analyze-images- computer-vision/2-image-analysis-azure",
        "references": ""
    },
    {
        "question": ": Which machine learning model is suitable for predic ting numeric values?",
        "options": [
            "A. Classification",
            "B. Regression",
            "C. Time series forecasting",
            "D. Clustering"
        ],
        "correct": "B. Regression",
        "explanation": "Explanation Regression is used for predicting numer ic values. Reference Link: https://docs.microsoft.c om/en- us/learn/modules/use-automated-machine-learning/dat a",
        "references": ""
    },
    {
        "question": ": User can use automated machine learning to train mo dels for below problems. Choose the correct option.",
        "options": [
            "A. Regression",
            "B. Classification",
            "C. Time series forecasting",
            "D. Clustering"
        ],
        "correct": "",
        "explanation": "Explanation User can use automated machine learning  to train models for: Classification (predicting ca tegories or classes) Regression (predicting numeric values) Tim e series forecasting (regression with a time-series element, enabling you to predict numeric values at a future point in time) Reference Link: https://docs.microso ft.com/en- us/learn/modules/use-automated-machine-learning/dat a",
        "references": ""
    },
    {
        "question": ": You want to use the Computer Vision service to iden tify the location of individual items in an image. Which of the following features should you retrieve ?",
        "options": [
            "A. All of the above",
            "B. Categories",
            "C. Objects D. Tags"
        ],
        "correct": "C. Objects D. Tags",
        "explanation": "Explanation Computer Vision returns objects with a bounding box to indicate their location in the imag e. Reference Link: https://docs.microsoft.com/en-us/le arn/modules/analyze-images-computer-vision/2-image- analysis-azure",
        "references": ""
    }
]