I have not yet found a course that can cover machine learning and also explains the Maths needed to understand this.This course is no exception. Its extremely difficult for a programmer with no solid footing in Maths to understand it. Any help is a lot appreciated
True, very true and you'll hit that language barrier in no time. The courses, mostly, provide hands-on experience and don't explain, say for example, what does standard deviation mean?
But this is a good news/bad news kind of thing. Bad news, you need some statistics education to make a sense of what your computer is telling you. Good news, that mathematics isn't "high-grade" mathematics involving integrals and other stuff (as far as I can see anyway).
After I finish those I'll move to Kirill Eremenko's a-z courses on Machine Learning, AI and Deep Learning. I've found that even though they teach cool tricks and some basics before going in detail, that basics part didn't contain enough information for me as a new student. So I feel if you have some proper background in stats and python data analysis you can skip the parts I mentioned and go straight to a-z courses.
Thanks for your insights. I was wondering if one also needs a footing in vector calculus / linear algebra / integrals and other such words I have no idea about.
Also Kirill Eremenko has 38 courses listed. In what order should one take them?
I sympathize, but do keep in mind that it would be very difficult to teach all the math at the same time. Imagine trying to run a course in French on analytic philosophy. If your students didn't know much French coming in, you'd be in a tough spot.
I understand. I see so many people joining the ML / AI bandwagon and I wonder if so many people really understand the maths behind it or is it as simple as calling a function?