Notes from the Stanford machine learning course (by Liam).
<aside> 😴 This course is on hold since November 4, 2020 while I work on my company!
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Table of contents:
Notes taken while working through the course. If the status is "👀reviewing", I still need to go over the notes and consolidate them into Algorithms and Definitions.
Complete notes on the various algorithms and equations. These are live notes that will be updated as more modules built upon them. They may contain material from multiple modules.
Overview on terms or definitions from the course. For symbols used in the notes, see the Notation table.
GitHub Repository - where I host the supplementary Jupyter notebooks and code examples
Jupyter Notebook Viewer - for Python implementations of various algorithms
Octave/MATLAB Examples - implementations of various algorithms used in the course
Excalidraw - used for all the illustrations and graphs