Stanford Machine Learning Course
Stanford’s Machine Learning course taught by professor Andrew Ng has been made freely available on the web through two sources.
Stanford Engineering Everywhere (SEE)
SEE is a program run by Stanford where they make recordings of some of their engineering lectures freely available.
This course consists of YouTube videos which are recordings of the actual lecture with chalkboards and an audience. There are also detailed lecture notes provided along with every lecture, as well as review notes and assignments.
The main advantage to this source for the material is that all of the lectures are immediately available, and you can take however long you want to go over the material.
_Stanford Class - _This is the website for the actual course at Stanford. I haven’t made use of this page yet (all of the material seems to be available on the SEE page), but I’ve included it just in case.
This course is run in sessions (with a start date), and you get a certificate of completion from the instructor.
The material has a lot of similarities, but has been modified to be more accessible.
One of the most notable differences in the content is that the YouTube videos don’t cover Neural Networks (except for a brief mention), whereas the Coursera course does.
If you think you can manage the course schedule, then this is definitely the better source for the material.
My posts so far are based on the YouTube lectures.
The lecture notes provided for this class are _excellent. _For this reason, my posts on these lectures aren’t comprehensive notes on the discussion but rather serve the following purposes:
To point to all of the relevant reference material that is helpful for understanding the lecture, including the course lecture notes, review materials, and even lecture notes from other students published online.
To provide a basic overview of the lecture, and occasionally to explain concepts in a way that I find more intuitive.