This repository contains a data science project focused on predicting house prices in Bengaluru, India. The project utilizes machine learning algorithms, specifically linear regression, to forecast house prices based on various features such as square footage, number of bedrooms, bathrooms, location, and other relevant factors affecting house prices in the region.
- Predicts house prices in Bengaluru using machine learning techniques.
- Utilizes the linear regression algorithm to build predictive models.
- Includes data exploration, preprocessing, model training, and evaluation processes.
- Provides detailed documentation explaining the project workflow, data analysis, model selection, and evaluation metrics.
- Offers visualizations and insights derived from the analysis, as well as model performance metrics.
- This project was completed out of personal interest and as a way to apply the knowledge gained in data science. The project idea and dataset were inspired by resources from Code Basics, an online platform for learning data science and machine learning.