Any recommendations for a 101 book for neural nets for someone who is "just a programmer"? OP's tutorial is quite nice, but I love to read books and find it easier to learn from them.
It starts off with some tutorials using the Keras library, and then gets into the math later on.
By the end of the book, you create multiple different types of neural networks for identifying images, text, and more! I highly recommend it.
Fastai is top down: learn to use practical ML with abstractions, and then dig deeper and explain as needed.
I preferred fastai's approach, even though I enjoyed both. Ng's could be a bit too low level and fundamental for what I wanted to learn.
I tried Fast AI, but it seems to be trying too hard to take out the math, which oddly for me (as a STEM grad) makes it much more difficult to understand.
Had to stop when I saw him using Excel spreadsheets to explain convolution.