This is a python implementation of Linear Regression. This repository is based on linear_regression_demo. The original code doesn't actually implement all the fundamental codes. Of course, we can use libraries like sklearn to use linear regression. But I hope this codes help you study the basic principal of it.
To use the demo.py which uses sklearn, you need to install it first. And linear-regression.py uses libraries for data-reading(pandas), data-processing(numpy) and visualizing(matplotlib). So you need to install three dependencies below.
- pandas
- numpy
- scikit-learn
- matplotlib
You can just run
pip install -r requirements.txt
in terminal to install the necessary dependencies. Here is a link to pip if you don't already have it.
Type python demo.py into terminal and you'll see the scatter plot and line of best fit appear.
And you can also type python linear-regression.py without using sklearn libraray. But you will see the same result of demo.py.
Enjoy the codes.