Housing Price Prediction - MLOps Workflow

This repository demonstrates a simple MLOps workflow for predicting housing prices based on features like area, bedrooms, and bathrooms.

Repository Contents

• Housing.csv: The dataset used for training the model.

• train.py: A script to train the linear regression model and save it as model.pkl.

• test_model.py: A script to test the trained model by predicting prices for sample inputs.

Usage Instructions

To run this project, you will need Python installed on your local machine. Follow these steps:

Clone the repository:

git clone https://github.com/<your-username>/housing-mlops-basic.git

cd housing-mlops-basic

Install the required Python libraries:
pip install pandas scikit-learn joblib

Run the training script:
python train.py

Run the test script:
python test_model.py

This will train a linear regression model and use it to predict housing prices.

Add a commit message like:
Added README.md with usage instructions

Ensure "Commit directly to the main branch" is selected.
Click "Commit new file".