Update pages/5_ML ALGORITHMS

pages/5_ML ALGORITHMS

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+import streamlit as st
+
+st.set_page_config(page_title="ML Algorithms", layout="centered")
+
+st.title("🤖 Machine Learning Algorithms Overview")
+
+st.markdown("""
+This app gives a quick overview of **core Machine Learning algorithms** and their types.
+Explore **Supervised** and **Unsupervised** learning with common algorithms like **KNN**, **SVM**, **Decision Trees**, etc.
+""")
+
+ml_type = st.selectbox("Select Type of Machine Learning", ["Supervised Learning", "Unsupervised Learning"])
+
+if ml_type == "Supervised Learning":
+    st.header("📘 Supervised Learning")
+    st.write("Supervised learning works with **labeled data**, where the goal is to predict a target (output) from input features.")
+
+    st.subheader("🔹 Common Algorithms:")
+    st.markdown("""
+    - **Linear Regression** → Predicts continuous values  
+    - **Logistic Regression** → Binary or multiclass classification  
+    - **K-Nearest Neighbors (KNN)** → Classifies based on closest data points  
+    - **Support Vector Machine (SVM)** → Classifies using hyperplanes  
+    - **Decision Tree** → Uses tree-based decision rules  
+    - **Random Forest** → Ensemble of decision trees  
+    """)
+
+    st.subheader("🛠️ Use Cases:")
+    st.markdown("""
+    - Email spam detection  
+    - House price prediction  
+    - Medical diagnosis  
+    - Loan approval  
+    """)
+
+elif ml_type == "Unsupervised Learning":
+    st.header("📙 Unsupervised Learning")
+    st.write("Unsupervised learning deals with **unlabeled data**. It finds hidden patterns, groupings, or structures in the data.")
+
+    st.subheader("🔹 Common Algorithms:")
+    st.markdown("""
+    - **K-Means Clustering** → Groups data into clusters  
+    - **Hierarchical Clustering** → Builds a tree of clusters  
+    - **DBSCAN** → Density-based clustering  
+    - **PCA (Principal Component Analysis)** → Reduces dimensionality  
+    """)
+
+    st.subheader("🛠️ Use Cases:")
+    st.markdown("""
+    - Customer segmentation  
+    - Market basket analysis  
+    - Anomaly detection  
+    """)
+
+st.markdown("---")
+st.caption("Made with ❤️ using Streamlit — for educational ML projects")