Update pages/Intro_DS.py

pages/Intro_DS.py

@@ -72,10 +72,8 @@ st.markdown("<p style='font-size: 16px; color: Blue; font-style: italic;'>"
            "Semi-Supervised Learning")
 st.markdown("<h3 style='text-align: left; color: Black;'>Examples of ML </h3>",unsafe_allow_html=True)
 st.markdown("<p style='font-size: 16px; color: Blue; font-style: italic;'>"
-           "Recommendation Systems (Netflix, YouTube, and Amazon):How It Works: Machine learning models use your previous behaviour (e.g., what you viewed or purchased) to propose new content or goods that you might enjoy.
-For example, Netflix recommends episodes based on what you've viewed, while Amazon sells things based on your browsing history."
-"Fraud detection (banking and credit cards),How it works: Machine learning algorithms examine transaction data for unexpected patterns that might signal fraud.
-For example, credit card firms utilise machine learning to detect potentially fraudulent transactions in real time, such as a card being used in two different places within minutes."
+"Recommendation Systems (Netflix, YouTube, and Amazon):How It Works: Machine learning models use your previous behaviour (e.g., what you viewed or purchased) to propose new content or goods that you might enjoy.For example, Netflix recommends episodes based on what you've viewed, while Amazon sells things based on your browsing history."
+"Fraud detection (banking and credit cards),How it works: Machine learning algorithms examine transaction data for unexpected patterns that might signal fraud.For example, credit card firms utilise machine learning to detect potentially fraudulent transactions in real time, such as a card being used in two different places within minutes."
 "</p>", 
     unsafe_allow_html=True)