Update pages/Machine learning VS Deep Learning.py

pages/Machine learning VS Deep Learning.py

@@ -1,46 +1,79 @@
 import streamlit as st
 
-# HTML code for a differences table
+# CSS style for the table
+css_style = """
+<style>
+table {
+    width: 100%;
+    border-collapse: collapse;
+    border: 1px solid black;
+}
+
+th {
+    background-color: #f2f2f2;
+    border: 1px solid black;
+    padding: 10px;
+    text-align: center;
+}
+
+td {
+    border: 1px solid black;
+    padding: 10px;
+}
+
+tr:nth-child(even) {
+    background-color: #f9f9f9;
+}
+
+tr:nth-child(odd) {
+    background-color: #ffffff;
+}
+</style>
+"""
+
+# HTML code for the differences table
 html_code = """
-<table style="width: 100%; border-collapse: collapse; border: 1px solid black;">
-    <tr style="background-color: #f2f2f2;">
-        <th style="border: 1px solid black; padding: 10px; text-align: center;">Aspect</th>
-        <th style="border: 1px solid black; padding: 10px; text-align: center;">Machine Learning (ML)</th>
-        <th style="border: 1px solid black; padding: 10px; text-align: center;">Deep Learning (DL)</th>
+<table>
+    <tr>
+        <th>Aspect</th>
+        <th>Machine Learning (ML)</th>
+        <th>Deep Learning (DL)</th>
     </tr>
     <tr>
-        <td style="border: 1px solid black; padding: 10px;">Definition</td>
-        <td style="border: 1px solid black; padding: 10px;">A subset of AI focused on enabling systems to learn from data.</td>
-        <td style="border: 1px solid black; padding: 10px;">A subset of ML that uses neural networks to process data.</td>
+        <td>Definition</td>
+        <td>A subset of AI focused on enabling systems to learn from data.</td>
+        <td>A subset of ML that uses neural networks to process data.</td>
     </tr>
-    <tr style="background-color: #f9f9f9;">
-        <td style="border: 1px solid black; padding: 10px;">Data Dependency</td>
-        <td style="border: 1px solid black; padding: 10px;">Performs well on small to medium-sized datasets.</td>
-        <td style="border: 1px solid black; padding: 10px;">Requires large datasets to perform effectively.</td>
+    <tr>
+        <td>Data Dependency</td>
+        <td>Performs well on small to medium-sized datasets.</td>
+        <td>Requires large datasets to perform effectively.</td>
     </tr>
     <tr>
-        <td style="border: 1px solid black; padding: 10px;">Model Complexity</td>
-        <td style="border: 1px solid black; padding: 10px;">Uses simple algorithms like linear regression or decision trees.</td>
-        <td style="border: 1px solid black; padding: 10px;">Utilizes complex architectures like CNNs and RNNs.</td>
+        <td>Model Complexity</td>
+        <td>Uses simple algorithms like linear regression or decision trees.</td>
+        <td>Utilizes complex architectures like CNNs and RNNs.</td>
     </tr>
-    <tr style="background-color: #f9f9f9;">
-        <td style="border: 1px solid black; padding: 10px;">Computation Power</td>
-        <td style="border: 1px solid black; padding: 10px;">Less computationally intensive.</td>
-        <td style="border: 1px solid black; padding: 10px;">Highly computationally intensive, often requires GPUs.</td>
+    <tr>
+        <td>Computation Power</td>
+        <td>Less computationally intensive.</td>
+        <td>Highly computationally intensive, often requires GPUs.</td>
     </tr>
     <tr>
-        <td style="border: 1px solid black; padding: 10px;">Feature Engineering</td>
-        <td style="border: 1px solid black; padding: 10px;">Feature engineering is essential for performance.</td>
-        <td style="border: 1px solid black; padding: 10px;">Automatically learns features from data.</td>
+        <td>Feature Engineering</td>
+        <td>Feature engineering is essential for performance.</td>
+        <td>Automatically learns features from data.</td>
     </tr>
-    <tr style="background-color: #f9f9f9;">
-        <td style="border: 1px solid black; padding: 10px;">Applications</td>
-        <td style="border: 1px solid black; padding: 10px;">Fraud detection, recommendation systems, etc.</td>
-        <td style="border: 1px solid black; padding: 10px;">Image recognition, natural language processing, etc.</td>
+    <tr>
+        <td>Applications</td>
+        <td>Fraud detection, recommendation systems, etc.</td>
+        <td>Image recognition, natural language processing, etc.</td>
     </tr>
 </table>
 """
 
-# Render the HTML in Streamlit
-st.markdown(html_code, unsafe_allow_html=True)
+# Inject CSS into Streamlit
+st.markdown(css_style, unsafe_allow_html=True)
 
+# Render the HTML in Streamlit
+st.markdown(html_code, unsafe_allow_html=True)