This project contains a Python implementation of a linear regression model developed from scratch, using mathematical formulas and optimized with a custom implementation of the gradient descent algorithm.
The model was developed to predict the prices of houses in the Boston area using the Boston Housing Dataset from scikit-learn (sklearn). The dataset contains 506 samples of houses, with 13 features such as crime rate, average number of rooms, and distance to employment centers, among others.
No Machine Learning Framework was used in the making of this project as Scikit-learn was only used to load the dataset into NumPy arrays.
To run the project, you will need the following Python packages:
- NumPy
- Pandas
- Matplotlib
- Scikit-learn (only to load the Boston Housing Dataset)
You can install these packages using pip, conda, or any other package manager.
The project contains the following file:
- solution.ipynb: a Jupyter Notebook with the code and documentation for the project.