Machine learning notes

You can find the Notion notebook with all the course notes here.

This repository hosts supplementary Jupyter notebooks and code examples for notes from the Stanford machine learning course.

Quick links:

• Course notes
• Jupyter notes (links below will point to specific notebooks)

Notes

Jupyter notebooks containing some Python code that suppliments the Notion notes.

• Cost function
• Gradient descent
• Linear algebra
• Linear regression
• Normal equation

Octave examples

The folder octave_examples will contain some example Octave/MATLAB functions for certain algorithms covered in the course.

• costFunction
• gradientDescent
• meanStandardNormalize
• normalEquation

Assignments

I have git ignored the assignments folder since it contains answers to the programming assignments. I highly encourage doing the course yourself. It's free!