Re:Introduction to Machine Learning for Coders: Launch
by jph00 on Saturday September 29, 2018 @07:22AM
(#18099805)
The biggest difference is that Andrew's teaching style tends to be more bottom-up and math-first, whereas mine is top-down and code-first. They both should give you a thorough foundation if you complete the course. Why not watch the first lesson of each and see which presentation suits you best?
Sometimes I'll assume some understanding of basic linear algebra or probability distributions when explaining why something works. Particularly for the naive Bayes section.
The first half of the course assumes only high school math. If you get to a bit where I mention some math you're less confident of, just search for that term on Khan Academy for a lesson. Or just skip that explanation in the course - it won't stop you from being able to apply the concepts even if you don't always follow the math.
1. How exactly it is different from Andrew NG's course, other than Octave/Matlab vs Python? As someone who is new to ML and wants an introduction, I am now confused which course I should do.
2. What are the math prerequisites? Do you also cover them in the course or is there any list materials available to prep?