Update app.py

app.py

@@ -6,7 +6,7 @@ def generate_ml_blog():
     # Introduction to Machine Learning (ML)
     Machine Learning (ML) is a subset of Artificial Intelligence (AI) that enables computers to learn from data and make predictions or decisions without being explicitly programmed. It has revolutionized many industries and plays a crucial role in technologies such as self-driving cars, recommendation systems, and facial recognition.
 
-    ## Types of Machine Learning
+    ### Types of Machine Learning
     There are three main types of machine learning:
 
     1. **Supervised Learning**:
@@ -18,7 +18,7 @@ def generate_ml_blog():
     3. **Reinforcement Learning**:
         Reinforcement learning involves an agent that learns to make decisions by interacting with an environment to maximize a cumulative reward. It is widely used in robotics, game AI, and real-time decision-making systems.
 
-    ## Popular Machine Learning Algorithms
+    ### Popular Machine Learning Algorithms
     Some of the most commonly used ML algorithms include:
 
     - **Linear Regression**: A simple algorithm used for predicting continuous values.
@@ -28,7 +28,7 @@ def generate_ml_blog():
     - **Support Vector Machines (SVM)**: A powerful classifier that works well for high-dimensional spaces.
     - **Neural Networks**: A set of algorithms, modeled after the human brain, that are used for complex tasks like image and speech recognition.
 
-    ## Applications of Machine Learning
+    #### Applications of Machine Learning
     Machine learning is used in a wide variety of fields, including:
 
     - **Healthcare**: ML is used for predicting diseases, recommending treatments, and analyzing medical data.
@@ -36,7 +36,7 @@ def generate_ml_blog():
     - **E-commerce**: ML powers recommendation systems, personalized marketing, and customer support chatbots.
     - **Self-driving Cars**: ML algorithms help autonomous vehicles navigate and make real-time decisions.
 
-    ## Conclusion
+    ### Conclusion
     Machine learning continues to evolve, with new algorithms, techniques, and applications emerging regularly. As the amount of data grows and computational power increases, the potential of ML to impact industries and improve our daily lives is limitless.
     '''
     
@@ -44,9 +44,9 @@ def generate_ml_blog():
 
 # Streamlit UI Components
 
-st.markdown("<h1 style='text-align: center; color: grey;'>Machine Learning (ML)</h1>", unsafe_allow_html=True)
+st.markdown("<h1 style='text-align: center; color: orange;'>Machine Learning (ML)</h1>", unsafe_allow_html=True)
 
-st.markdown("<h2 style='text-align: center; color: black;'>Introduction</h2>", unsafe_allow_html=True)
+st.markdown("<h2 style='text-align: center; color: orange;'>Introduction</h2>", unsafe_allow_html=True)
 
 st.markdown(generate_ml_blog())