Learning suggestions for AI and neural networks for a mathematician I am a mathematician who has done programming in Python, Java, and R. I would like to learn to make neural networks and artificial intelligence. Are there any good books for self learning AI for a person like me who loves learning theory behind neural networks, and who can learn by proving theorems and thinking the theory behind AI? When I just read Tensorflow's or Keras's documentation, I found that I couldn't understand how the networks work.
The online textbook Neural Networks and Deep Learning by Michael Nielsen is quite good for mathematical content. It assumes the reader understands calculus, but requires no prior knowledge of machine learning. The book's own introduction explains fairly well what the book is about:


  The purpose of this book is to help you master the core concepts of neural networks, including modern techniques for deep learning. ... One conviction underlying the book is that it's better to obtain a solid understanding of the core principles of neural networks and deep learning, rather than a hazy understanding of a long laundry list of ideas. If you've understood the core ideas well, you can rapidly understand other new material.