Interesting, I found the course disappointingly shallow. I did do it soon after it came out, maybe it got much better with time. I also have a background / job in statistics, though not ML as such.
While it does talk through the basics of ML, it is really barely a taster. It doesn’t leave you with any skills, other than, if you buy a book and work through it, you will know what a “decision tree” is ahead of time.
With something like ML, the real value is in the deep nitty gritty, building intuition about methods you use, fighting the unfair battle against broken data etc, and all those things were missing to me.
Have you tried the deep learning courses? They steer away from statistics and proofs, but all the math required to build a convoluted network is covered. Lib use is very low level at first; not too far removed from doing it all from scratch it you really wanted to waste the time.
While it does talk through the basics of ML, it is really barely a taster. It doesn’t leave you with any skills, other than, if you buy a book and work through it, you will know what a “decision tree” is ahead of time.
With something like ML, the real value is in the deep nitty gritty, building intuition about methods you use, fighting the unfair battle against broken data etc, and all those things were missing to me.