Update app.py

app.py

@@ -136,17 +136,38 @@ if selected_menu == "Introduction":
 elif selected_menu == "The Model":
     st.title("Neural Networks")
 
+    st.write("Neural networks are computational models designed to mimic the workings of the human brain. They consist of interconnected nodes, called neurons, which work together to process information and learn from data.")
+    st.write(" ")
+
+    st.image("neural_net.png")
+
+    st.subheader("Learning in Neural Networks")
+
+    st.write("**Forward Pass:** The input data is passed through the network, layer by layer, producing an output.")
+    st.write(" ")
+
+    st.video("ezgif-6-7827342558.mp4")
+
+    st.write("**Loss Function:** The network's output is compared to the actual label (for supervised learning), and a loss value is computed to quantify the difference.")
+    st.write(" ")
+
+    st.write("**Backward Pass (Backpropagation):** The loss is used to calculate the gradients, which indicate how much each weight should be adjusted to reduce the error.")
+    st.write(" ")
+
+    st.write("**Optimization:** An optimization algorithm, such as Stochastic Gradient Descent (SGD) or Adam, adjusts the weights based on the gradients, iteratively reducing the loss.")
+    st.write(" ")
+        
     st.subheader("Key Terms")
 
-    st.write("Convolution Operation: A process in a CNN where a small grid moves over the image and simplifies it by focusing on the important details, like edges and colors, helping the network understand the image better.")
+    st.write("**Convolution Operation:** A process in a CNN where a small grid moves over the image and simplifies it by focusing on the important details, like edges and colors, helping the network understand the image better.")
     st.write(" ")
-    st.write("Filter/Kernel: A tiny grid used in CNNs that looks at small parts of the image to find specific features like lines or corners.")
+    st.write("**Filter/Kernel:** A tiny grid used in CNNs that looks at small parts of the image to find specific features like lines or corners.")
     st.write(" ")
-    st.write("Feature Map: The result you get after a filter scans the image. It shows what the filter noticed, like different textures or shapes in the picture.")
+    st.write("**Feature Map:** The result you get after a filter scans the image. It shows what the filter noticed, like different textures or shapes in the picture.")
     st.write(" ")
-    st.write("Pooling: A step used to make the image data smaller and easier to manage by simplifying the details but keeping the important parts. It helps the network process images faster.")
+    st.write("**Pooling:** A step used to make the image data smaller and easier to manage by simplifying the details but keeping the important parts. It helps the network process images faster.")
     st.write(" ")
-    st.write("Backpropagation: A way the network learns from mistakes. It looks at errors it made in recognizing images and adjusts itself to do better next time.")
+    st.write("**Backpropagation:** A way the network learns from mistakes. It looks at errors it made in recognizing images and adjusts itself to do better next time.")
 
     image_path_1 = 'Screenshot 2024-05-03 at 08.01.06.png'
     image_1 = Image.open(image_path_1)