🏠 California Housing Price Prediction

🎯 Objective

To predict median house prices in California using a linear regression model, based on features such as income, location, and housing characteristics.

📊 Dataset

We used the California Housing Dataset provided by Scikit-learn.
📎 Dataset Link

🛠️ Tech Stack

• Python
• Scikit-learn
• Pandas & NumPy
• Matplotlib / Seaborn (for visualization)
• Jupyter Notebook

📈 Results

• R² Score: 0.624
  ➤ The model explains 62.4% of the variance in housing prices.

• Key Insight:
  Median Income is the most influential feature, as shown by:

  • Its high coefficient in the model
  • A clear positive trend in its scatter plot against house prices

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