This is the code for the "How to Do Linear Regression the Right Way" live session by Siraj Raval on Youtube
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README.md

linear_regression_live

This is the code for the "How to Do Linear Regression the Right Way" live session by Siraj Raval on Youtube

Overview

This is the code for this video on Youtube by Siraj Raval. I'm using a small dataset of student test scores and the amount of hours they studied. Intuitively, there must be a relationship right? The more you study, the better your test scores should be. We're going to use linear regression to prove this relationship.

Here are some helpful links:

Gradient descent visualization

https://raw.githubusercontent.com/mattnedrich/GradientDescentExample/master/gradient_descent_example.gif

Sum of squared distances formula (to calculate our error)

https://spin.atomicobject.com/wp-content/uploads/linear_regression_error1.png

Partial derivative with respect to b and m (to perform gradient descent)

https://spin.atomicobject.com/wp-content/uploads/linear_regression_gradient1.png

Dependencies

  • numpy

Python 2 and 3 both work for this. Use pip to install any dependencies.

Usage

Just run python3 demo.py to see the results:

Starting gradient descent at b = 0, m = 0, error = 5565.107834483211
Running...
After 1000 iterations b = 0.08893651993741346, m = 1.4777440851894448, error = 112.61481011613473

Credits

Credits for this code go to mattnedrich. I've merely created a wrapper to get people started.