A syllabus for a half-semester course on prediction from data.
It would be pretty valuable to have the course be aopen access. It seems to be approaching ML from a foundational perspective which is quite unique.
Thanks! My plans are:
(a) I'll do my best to summarize every lecture on this substack.
(b) The course is going to be strongly tied to my book with Mortiz Hardt. Available for free here: https://mlstory.org/
(c) For any supplementary material that's not in the book and not available in another source, I'll link to notes on substack.
(d) I'm aspiring to release a set of problems for the course at some point this academic year.
The last one is very aspirational. But (a)-(c) will happen.
It would be pretty valuable to have the course be aopen access. It seems to be approaching ML from a foundational perspective which is quite unique.
Thanks! My plans are:
(a) I'll do my best to summarize every lecture on this substack.
(b) The course is going to be strongly tied to my book with Mortiz Hardt. Available for free here: https://mlstory.org/
(c) For any supplementary material that's not in the book and not available in another source, I'll link to notes on substack.
(d) I'm aspiring to release a set of problems for the course at some point this academic year.
The last one is very aspirational. But (a)-(c) will happen.