If you want to learn the fundamentals of ML I recommend a book, such as Deep Learning: Foundations and Concepts by Chris Bishop. If you insist on staying online, one option is https://course.fast.ai/

If you don't know ML I don't think you're going to learn much through ad hoc demos.

Checked out the book on your recommendation, and they even have a free online option on their site! Very generous: https://www.bishopbook.com/

I remember sitting in the senior study lounge reading the previous Bishop book and implementing the perceptron from it, 22 years ago: https://github.com/llimllib/personal_code/blob/945b017b2915c...

(before numarray and numpy merged!)

This book equipped me with the right intuition and tools to visualize machine learning. I wish I was smart enough to hold it all together.

>I wish I was smart enough to hold it all together.

I used to have a wife, but they took her in the divorce!

The human mind isn't very good at correlating its contents[0]. You can "know" something for years without realizing its implications.

The human mind traverses its knowledge like a man with a small flashlight in total darkness. Our beam of attention is small and narrow, so you need to put the right things in it, or the magic doesn't happen.

This has important implications for learning. I don't know what they are though.

Probably something like, "you can know something without knowing what it means." You haven't connected it to the things it's supposed to be connected to yet. I don't know how to fix that though. (Something involving the Feynman technique, maybe?)

[0] H.P. Lovecraft quote - https://www.goodreads.com/quotes/193944-the-most-merciful-th...

I didn't know Bishop had released a new textbook. I will have to take a look at it. I wasn't the biggest fan of his Pattern Recognition book as I found it overly dense. I much preferred the Murphy and Alpaydin books.

EDIT: His son is co-author?

I still find his pattern recognition book useful and informative. It may be dense, but some of us consider that a positive for 'reference' literature. That book was one of very few that still holds up well fr when it was published - truly in on of the last "dark ages" of ML.

I think those down voting you are perhaps overly eager. I upvoted. Grab "Deep Learning" - you'll find it useful, imteresting, and likely less 'dense' in the negative sense!

Appreciate your comment. I skimmed the online version and it covers all the 2010s era developments all the way to Transformers which is enough to earn it a spot on my bookshelf.

> Grab "Deep Learning" - you'll find it useful, imteresting, and likely less 'dense' in the negative sense!

Absolutely! I just ordered it and it's enroute :)

This fast AI course looks soo good man! Definitely I will start learning soon. Thank you!