Update app.py

app.py

@@ -224,11 +224,64 @@ def neural_networks():
     return neural
 
 
-  # Call the function to display the image
-st.markdown("<h1 style='text-align: center; color: orange;'>Machine Learning (ML)</h1>", unsafe_allow_html=True)
-st.markdown(generate_ml_blog())
 
-# Define a dictionary to map page names to functions
+
+import streamlit as st
+
+# Define page functions (Make sure these functions are defined elsewhere in your code)
+def introduction_to_ml():
+    st.title("Introduction to Machine Learning (ML)")
+    # Add content for the Introduction page
+
+def supervised_learning():
+    st.title("Supervised Learning")
+    # Add content for Supervised Learning
+
+def unsupervised_learning():
+    st.title("Unsupervised Learning")
+    # Add content for Unsupervised Learning
+
+def reinforcement_learning():
+    st.title("Reinforcement Learning")
+    # Add content for Reinforcement Learning
+
+def linear_regression():
+    st.title("Linear Regression")
+    # Add content for Linear Regression
+
+def logistic_regression():
+    st.title("Logistic Regression")
+    # Add content for Logistic Regression
+
+def decision_trees():
+    st.title("Decision Trees")
+    # Add content for Decision Trees
+
+def knn():
+    st.title("K-Nearest Neighbors (KNN)")
+    # Add content for K-Nearest Neighbors
+
+def svm():
+    st.title("Support Vector Machines (SVM)")
+    # Add content for SVM
+
+def neural_networks():
+    st.title("Neural Networks")
+    # Add content for Neural Networks
+
+# Sidebar for content navigation
+st.sidebar.header("📚 Contents")
+
+# Grouping the types of machine learning into one section
+types_of_ml = st.sidebar.radio("📊 Types of Machine Learning", 
+                               ["Supervised Learning", "Unsupervised Learning", "Reinforcement Learning"])
+
+# Grouping other topics under a separate section
+popular_algorithms = st.sidebar.radio("🚀 Popular Algorithms", 
+                                      ["Linear Regression", "Logistic Regression", "Decision Trees", 
+                                       "K-Nearest Neighbors (KNN)", "Support Vector Machines (SVM)", "Neural Networks"])
+
+# Mapping page functions to selection
 pages = {
     "Introduction": introduction_to_ml,
     "Supervised Learning": supervised_learning,
@@ -242,32 +295,28 @@ pages = {
     "Neural Networks": neural_networks
 }
 
-# Sidebar for content navigation
-st.sidebar.header("📚 Contents")
-st.sidebar.markdown("""
-- 🔍 [Introduction](#Introduction-to-Machine-Learning-ML)
-- 🧠 [Types of Machine Learning](#Types-of-Machine-Learning)
-    - 📊 [Supervised Learning](#Supervised-Learning)
-    - 🔗 [Unsupervised Learning](#Unsupervised-Learning)
-    - 🕹️ [Reinforcement Learning](#Reinforcement-Learning)
-- 🚀 [Popular Algorithms](#Popular-Machine-Learning-Algorithms)
-    - 🔧 [Linear Regression](#Linear-Regression)
-    - ✔️ [Logistic Regression](#Logistic-Regression)
-    - 🌳 [Decision Trees](#Decision-Trees)
-    - 🔍 [K-Nearest Neighbors (KNN)](#K-Nearest-Neighbors-KNN)
-    - ✂️ [Support Vector Machines (SVM)](#Support-Vector-Machines-SVM)
-    - 🧠 [Neural Networks](#Neural-Networks)
-""")
-
 # Main content area
 st.markdown("<h1 style='text-align: center; color: orange;'>Machine Learning (ML)</h1>", unsafe_allow_html=True)
 st.markdown(generate_ml_blog())
 
-# Sidebar radio button to select the page
-selected_page = st.sidebar.radio("Select Section", list(pages.keys()))
+# Use the selected type of machine learning or algorithm to show the content
+if types_of_ml in pages:
+    pages[types_of_ml]()
+
+if popular_algorithms in pages:
+    pages[popular_algorithms]()
+
+# Display the page content based on the selected page
+st.markdown(f"<h2 style='text-align: center; color: orange;'>{types_of_ml}</h2>", unsafe_allow_html=True)
+content_function = pages[types_of_ml]  # Get the corresponding function
+st.markdown(content_function())
 
-# Display the content based on the selected page
-st.markdown(f"<h2 style='text-align: center; color: orange;'>{selected_page}</h2>", unsafe_allow_html=True)
-content_function = pages[selected_page]  # Get the corresponding function
+# Alternatively, display the popular algorithms' content as well
+st.markdown(f"<h2 style='text-align: center; color: orange;'>{popular_algorithms}</h2>", unsafe_allow_html=True)
+content_function = pages[popular_algorithms]  # Get the corresponding function
 st.markdown(content_function())
 
+
+
+
+