Machine Learning

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📌 TASK 01: House Price Prediction

Built a Linear Regression model to predict house prices based on:

• Square footage
• Number of bedrooms
• Number of bathrooms

✅ Learned: Supervised Learning
📊 Evaluated Using: Mean Squared Error (MSE), R² Score
📈 Visualization: Compared predicted vs actual prices using line plots.

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📌 TASK 02: Customer Segmentation Using K-Means

Applied K-Means Clustering to segment customers based on spending behavior.

✅ Learned: Unsupervised Learning
🔍 Approach: Optimized number of clusters using Elbow Method
📊 Visualization: Scatter plots to show clustered segments

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🛠️ Tools & Technologies

• Python
• Pandas
• Matplotlib
• Seaborn
• Scikit-learn

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