Update app.py

app.py

@@ -1,11 +1,11 @@
 import streamlit as st
 import base64
 
-# Set page config
+# Set Streamlit page config
 st.set_page_config(page_title="🧠 Neural Network Playground", layout="wide")
 
-# Background image function
-def set_background(image_path):
+# Function to apply blurred background image
+def set_background_blur(image_path):
     with open(image_path, "rb") as image_file:
         encoded = base64.b64encode(image_file.read()).decode()
 
@@ -18,41 +18,63 @@ def set_background(image_path):
             background-repeat: no-repeat;
             background-position: center;
             background-attachment: fixed;
+            filter: blur(6px);
+        }}
+        .main > div {{
+            background-color: rgba(255, 255, 255, 0.85);
+            padding: 2rem;
+            border-radius: 15px;
+        }}
+        .typing {{
+            font-family: 'Courier New', monospace;
+            color: #6A0DAD;
+            font-size: 45px;
+            font-weight: bold;
+            white-space: nowrap;
+            overflow: hidden;
+            border-right: 0.15em solid orange;
+            width: 0;
+            animation:
+                typing 3.5s steps(40, end) forwards,
+                blink-caret 0.75s step-end infinite;
+        }}
+        @keyframes typing {{
+            from {{ width: 0 }}
+            to {{ width: 100% }}
+        }}
+        @keyframes blink-caret {{
+            from, to {{ border-color: transparent }}
+            50% {{ border-color: orange }}
         }}
         </style>
         """,
         unsafe_allow_html=True
     )
 
-# Set background image
-#set_background(r"ann.jpeg")
-
-
-# --- Project README/Intro Section ---
-
-st.markdown("""
-# 🧠 Interactive Neural Network Playground
-A Python app that lets users explore how neural networks learn by adjusting hyperparameters and visualizing the results.
----
-### 🚀 What It Does
-- Lets you choose:
-    - **Dataset**: moons, circles, blobs, classification  
-    - **Learning rate**  
-    - **Activation**: ReLU, Sigmoid, Tanh  
-    - **Train-test split ratio**  
-    - **Batch size**
-    - **Epochs**:  
-    - **Hidden Layes**  
-    - **Number of Neurons**
-    
-    
-- Builds & trains a TensorFlow/Keras neural network on synthetic data.
-- Visualizes:
-    - 🌈 **Decision boundaries** (how the model classifies the space)
-    - 📈 **Training vs testing error** across epochs
----
-### 🎯 Why It’s Useful
-✅ Understand hyperparameter effects  
-✅ See overfitting vs underfitting visually  
-✅ Learn neural network behavior interactively
-""")
+# Set background image (optional - uncomment below)
+# set_background_blur("ann.jpeg")
+
+# Typing animation title
+st.markdown("<div class='typing'>⚡ Neural Network Lab</div>", unsafe_allow_html=True)
+st.markdown("### 🧪 *Tinker. Train. Transform. — Explore neural networks like never before!*")
+
+# Add a horizontal line
+st.markdown("<hr style='border-top: 2px solid #bbb;'>", unsafe_allow_html=True)
+
+# Collapsible section for details
+with st.expander("📘 Click to Learn More About This App"):
+    st.markdown("""
+    ### 🔧 What You Can Do Here
+    - 🧩 Choose from datasets like **Moons**, **Circles**, or **Custom Classification**
+    - 🔢 Tweak model structure: layers, neurons, activations, learning rate
+    - 📉 Train interactively and watch how it learns over time
+    - 🎨 Visualize decision boundaries and loss curves instantly
+
+    ### 🎯 Why Use This?
+    - 👀 See neural network behavior come to life
+    - 🧠 Understand how changes impact learning
+    - 🎓 Perfect for education, demos, and self-learning
+    """)
+
+# Add another subtle separator
+st.markdown("<hr style='border-top: 1px dashed #ccc;'>", unsafe_allow_html=True)