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Good post. I want to add several great resources. - Grokking Deep Learning link This is a fantastic book that assumes no prerequisites other than knowing python, and takes you through the fundamentals of DL. It has very intuitive and easy to follow explanations, and doesn't use any libraries other than NumPy, so you're building the whole thing yourself, from scratch. - Deep Learning With Python link This is kind of the opposite of the previous one, it doesn't go into math and theory, instead it guides you through building several practical projects with a very simple to use DL library(keras). It's a great way to gain practical experience in addition to theory from the previous book. Also has no prerequisites other than python, and makes it very easy to get started. - 3blue1brown videos on neural networks: link Extremely brilliant high-level concise overview of how ANNs work. I highly recommend you get started here. You should also check out his videos on calulus and linear algebra, they're fantastic way to learn the math you need. - Khan Academy videos - one of the easiest ways to learn the math prerequisites. Calculus: link Linear Algebra: link Probability and Statistics: link - Hands-On Machine Learning with Scikit-Learn and TensorFlow link I haven't read this one yet, but it looks very promising, and a lot of people seem to find it very useful. - Andrew Ng's Coursera course link Everyone knows about this one, I just think every article on AI resources shoul
