Delete 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")