Update app.py

app.py

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+import streamlit as st
+
+# Page settings
+st.set_page_config(
+    page_title="📘 ML Notes Hub",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# --- Custom CSS ---
+st.markdown("""
+    <style>
+    .main-title {
+        font-size: 3rem;
+        color: #004080;
+        font-weight: 700;
+        text-align: center;
+        margin-bottom: 0.5rem;
+    }
+    .subtitle {
+        font-size: 1.2rem;
+        color: #333333;
+        text-align: center;
+        margin-bottom: 2rem;
+    }
+    .note-box {
+        background-color: #f9f9f9;
+        padding: 1.5rem;
+        border-radius: 10px;
+        box-shadow: 0 2px 8px rgba(0,0,0,0.05);
+        margin-bottom: 1rem;
+    }
+    </style>
+""", unsafe_allow_html=True)
+
+# --- Sidebar Navigation ---
+st.sidebar.title("📚 ML Notebook")
+page = st.sidebar.radio("Go to", ["Home", "Supervised Learning", "Unsupervised Learning", "Evaluation Metrics", "Resources"])
+
+# --- Home Page ---
+if page == "Home":
+    st.markdown('<div class="main-title">📘 Machine Learning Notes</div>', unsafe_allow_html=True)
+    st.markdown('<div class="subtitle">Your personal guide to mastering ML concepts!</div>', unsafe_allow_html=True)
+
+    st.markdown("### 🚀 Why Use This App?")
+    st.markdown("""
+    - Concise, organized ML notes
+    - Easy to navigate concepts
+    - Interactive widgets (coming soon)
+    - Great for revision, projects, and interviews
+    """)
+
+    st.markdown('<div class="note-box">', unsafe_allow_html=True)
+    st.markdown("### 📌 Topics Covered:")
+    st.markdown("""
+    - 🔹 Supervised Learning  
+    - 🔹 Unsupervised Learning  
+    - 🔹 Model Evaluation Metrics  
+    - 🔹 Data Preprocessing  
+    - 🔹 Tips for Interviews  
+    - 🔹 Useful Resources  
+    """)
+    st.markdown('</div>', unsafe_allow_html=True)
+
+    st.markdown("🛠 *More features coming soon: interactive examples, quizzes, and more!*")
+
+# --- Additional Pages Placeholder ---
+elif page == "Supervised Learning":
+    st.title("🔍 Supervised Learning")
+    st.write("This section will contain detailed notes on regression, classification, and more.")
+
+elif page == "Unsupervised Learning":
+    st.title("🧩 Unsupervised Learning")
+    st.write("Learn about clustering, dimensionality reduction, and pattern discovery.")
+
+elif page == "Evaluation Metrics":
+    st.title("📏 Model Evaluation Metrics")
+    st.write("Accuracy, precision, recall, F1-score, confusion matrix and more.")
+
+elif page == "Resources":
+    st.title("📚 Resources")
+    st.markdown("""
+    - [Scikit-learn Docs](https://scikit-learn.org/)
+    - [Kaggle Courses](https://www.kaggle.com/learn)
+    - [Google ML Crash Course](https://developers.google.com/machine-learning/crash-course)
+    """)
+