Update pages/2_ML vs DL.py

pages/2_ML vs DL.py

@@ -2,14 +2,14 @@ import streamlit as st
 
 st.markdown("""
     <div style='text-align: center;'>
-        <h1 style='color: white;'>Difference between ML and DL</h1>
+        <h1 style='color: rainbow;'>Difference between ML and DL</h1>
     </div>
     """, unsafe_allow_html=True)
 
-st.header(":red-background[What is Machine learning?]")
+st.header(":blue-background[What is Machine learning?]")
 st.write(" ML involves algorithms that enable computers to learn from data and improve their performance over time without being explicitly programmed. It typically requires manual feature extraction and is suitable for structured data.Machine Learning  algorithms that learn from structured data to predict outputs and discover patterns in that data.")
-st.header(":red-background[What is Deep learning?]")
+st.header(":blue-background[What is Deep learning?]")
 st.write("DL is a specialized subset of ML that uses neural networks with multiple layers (hence deep) to automatically learn and extract features from unstructured data, such as images and text. It mimics the human brain's neural structure. Deep Learning algorithms based on highly complex neural networks that mimic the way a human brain works to detect patterns in large unstructured data sets.")
-st.header(":red-background[Difference between ML and DL:-]")
+st.header(":blue-background[Difference between ML and DL:-]")
 st.write("ML and DL are the tools by using which we can mimic/copy Natural Intelligence where in this process of mimicing/copying we learn learning ability. Machine Learning (ML) and Deep Learning (DL) are both subsets of Artificial Intelligence (AI), but they differ significantly in their methodologies, complexity, and applications. Understanding these differences is crucial for selecting the appropriate approach for specific tasks.")
 st.image("https://cdn-uploads.huggingface.co/production/uploads/66bc7901facf447e2ccaca9b/CFf7xz3YgnAArAQZK4m7h.png")