This is an organised repository containing all materials for the edX Columbia Machine Learning online course, publically available at:

https://www.edx.org/learn/machine-learning/columbia-university-machine-learning

This is to provide an additional download location for those who wish to use this course for self-study, and in the event that the course page is no longer active.

The course is free to audit, and so lecture slides and videos are available to watch for free. One can pay a fee to access the following features:

• Verified certificate of completion
• Proctored examination as an opportunity to consolidate knowledge
• Access that allows the ability to post questions for other course students and TAs to answer queries.
• Ability to submit homework assignments for grading with an autograding script.

As of 2023, this course was archived by edX, so it's not longer clear if public access is still possible.

This repository also contains the work I completed as part of self-study of this course. For further information, please visit my blog below:

For those looking to work through this course, this repository contains:

1. /lecture-slides - All 24 lecture slides.
2. /assignments - All 4 coding assignments, starter code files.
3. /self-study-scanned-notes - Handwritten notes for all the lectures.
4. /self-study-key-equations - Handwritten condensed notes for the proctored exam.
5. /self-study-completed-assignments - Completed coding assignments.

TODO:

• Upload the edX homework assignments as Markdown files.
• Write your blog page for this.