🏠 House Prices Prediction - Advanced Regression Techniques

Prodigy Infotech Machine Learning Task 1

Problem Statement

Implement a linear regression model to predict the prices of houses based on their square footage and the number of bedrooms and bathrooms.

📊 Dataset

This project uses the House Prices - Advanced Regression Techniques dataset from Kaggle:

House Prices Competition Link

🚀 How to Run

1. Clone the repository:

git clone https://github.com/SafalNarsingh/Prodigy_ML_01

2. Install dependencies:

  pip install numpy pandas matplotlib seaborn scikit-learn 

3. Launch jupyternotebook:

jupyter notebook house_prices.ipynb

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📁 File Structure

.
├── data_files/
│   ├── sample_submission.csv
│   ├── test.csv
│   └── train.csv
├── data_description.txt
├── house_prices.ipynb
└── readme.md

📦 Requirements

Make sure the following Python libraries are installed:

• numpy

• pandas

• matplotlib

• seaborn

• scikit-learn