I think FastAI lesson 3 in "Practical Deep Learning for Coders", has one of the most intuitive buildups of gradient descent and loss that I've seen. * Lecture [1] Book Chapter [2]
It doesn't go into the math but I don't think that's a bad thing for beginners.
If you want mathematical, 3blue1brown has a great series of videos [3] on the topic.
It doesn't go into the math but I don't think that's a bad thing for beginners.
If you want mathematical, 3blue1brown has a great series of videos [3] on the topic.
[1] https://www.youtube.com/watch?v=hBBOjCiFcuo&t=1932s
[2] https://github.com/fastai/fastbook/blob/master/04_mnist_basi...
[3] https://www.youtube.com/watch?v=aircAruvnKk
* I've been messing around with this stuff since 2016 and have done a few different courses like the original Andrew Ng course and more.