I’m very excited to announce the beginning of a new journey called the Machine Learning Foundations series. As discussed in the video announcement above, this series will initially consist of eight 3.5-hour classes offered within the O’Reilly online learning platform from late May through early September:

May 28th — Intro to Linear Algebra
June 4th — Linear Algebra II: Matrix Operations
June 11th — Calculus I: Limits & Derivatives
June 25th —Calculus II: Partial Derivatives & Integrals
July 8th —Probability & Information Theory
July 23rd —Intro to Statistics
August 12th —Algorithms & Data Structures
early September — Optimization

Each class will feature:

Rich, full-color illustrations
Hands-on code demos in Python
Fully worked-through pencil-and-paper questions and solutions

There are 605 seats available in each class. At the time of posting:

The first two classes (on algebra) have fewer than ten seats each
The second pair of classes (on calculus) have fewer than a hundred
Registration for the fifth and sixth class is open and seats are filling up quickly.

As I have bandwidth, I will be publishing all of this content as free YouTube video tutorials, so if you’ve missed the classes, don’t worry! I will also probably be offering the classes again at some point, and eventually all of the content will be brought together neatly as a book.

You can read more about the Machine Learning Foundations series — including a detailed syllabus for each class and the developing body of open-source code — in GitHub here.