Update pages/Life_cycle_of_ML.py

pages/Life_cycle_of_ML.py

@@ -1,5 +1,3 @@
-
-
 ## Shapes Representing the ML Life Cycle
 
 <svg width="600" height="300">
@@ -42,33 +40,19 @@
   </defs>
 </svg>
 """
-
 # Render HTML content in Streamlit
 st.markdown(html_content, unsafe_allow_html=True)
-
-
 # Render the SVG
 st.markdown(html_content, unsafe_allow_html=True)
-
 # Interactive buttons for stages
 st.subheader("Stages in ML Life Cycle")
 if st.button("Problem Statement"):
-    st.write("Understanding the problem and setting objectives for the ML model.")
 if st.button("Data Collection"):
-    st.write("Gathering relevant data for model training.")
 if st.button("Simple EDA"):
-    st.write("Initial analysis to understand the dataset's basic properties.")
 if st.button("Data Preprocessing"):
-    st.write("Cleaning the data to ensure it's in a usable format.")
 if st.button("EDA"):
-    st.write("Deeper analysis to gain insights and find patterns in the data.")
 if st.button("Feature Engineering"):
-    st.write("Creating new features or modifying existing ones to improve model performance.")
 if st.button("Training"):
-    st.write("Training machine learning models using the processed data.")
 if st.button("Testing"):
-    st.write("Evaluating the trained model using a test set to assess its performance.")
 if st.button("Deploying"):
-    st.write("Deploying the model to a production environment.")
 if st.button("Monitoring"):
-    st.write("Continuously monitoring the model's performance in the production environment.")