Update pages/introds.py

pages/introds.py

@@ -46,10 +46,10 @@ custom_css = f"""
 # Inject CSS into Streamlit app
 st.markdown(custom_css, unsafe_allow_html=True)
 
-# Header section
-st.markdown("<h1>Welcome to Data Science Introduction</h1>", unsafe_allow_html=True)
+# Header Section
+st.markdown("<h1>Welcome to Data Science and Deep Learning</h1>", unsafe_allow_html=True)
 
-# Main content
+# Content for Data Science
 st.markdown(
     """
     <div class="division">
@@ -81,18 +81,31 @@ st.markdown(
     unsafe_allow_html=True
 )
 
-# Header section for Deep Learning
-st.markdown("<h1>Welcome to Deep Learning</h1>", unsafe_allow_html=True)
-
-# Main content for Deep Learning
+# Content for Deep Learning
 st.markdown(
     """
-    <p>
-        Deep learning is an artificial intelligence (AI) method that teaches computers to process data in a way inspired by the human brain. 
-        Deep learning models can recognize complex patterns in images, text, sounds, and other data to produce accurate insights and predictions. 
-        You can use deep learning methods to automate tasks that typically require human intelligence, 
-        such as describing images or transcribing a sound file into text.
-    </p>
-    """,
+    <div class="division">
+        <h2>What is Deep Learning?</h2>
+        <p>
+            Deep learning is an artificial intelligence (AI) method that teaches computers to process data in a way inspired by the human brain. 
+            Deep learning models can recognize complex patterns in images, text, sounds, and other data to produce accurate insights and predictions. 
+            You can use deep learning methods to automate tasks that typically require human intelligence, such as describing images or transcribing sound files into text.
+        </p>
+        <ul>
+            <li><strong>Entertainment:</strong> Companies like Netflix and Spotify recommend relevant content based on user preferences.</li>
+            <li><strong>Natural Language Processing:</strong> Enables machines to understand and process human language, such as in translation or chatbots.</li>
+            <li><strong>Fraud Detection:</strong> Helps detect and prevent fraudulent activities using predictive analytics (e.g., PayPal).</li>
+        </ul>
+    </div>
+    <div class="division">
+        <h2>Key Steps in Deep Learning</h2>
+        <ul>
+            <li><strong>Data Acquisition:</strong> Gather data relevant to the problem you're solving. The amount of data depends on model complexity.</li>
+            <li><strong>Data Preprocessing:</strong> Split the data into training, validation, and test sets, and preprocess it for consistency.</li>
+            <li><strong>Model Building and Training:</strong> Define the neural network architecture and expose it to labeled data for training.</li>
+        </ul>
+    </div>
+    """
+    ,
     unsafe_allow_html=True
 )