The Book of Why

Writing a Go Interpreter Writing a Go Compiler No One Cares about Crazy People I Heard You Paint Houses UNIX: A History and a Memoir Red Famine: Stalin's War on Ukraine How Asia Works The Dream Machine Black Earth The Fabric of Reality Behave (tried twice, maybe third times a charm?) A Short History of Nearly Everything Stiff: The Curious Lives of Human Cadavers Genius: The Life and Science Richard Feynman Super Thinking Man's Search for Meaning The Cooking Gene The Vital Question: Why is Life The Way it Is (re-read) The Case Against Sugar The 15 Decisive Battles of the World The History of the Peloponnesian War The Beginning of Infinity The Book of Why

1. Grokking Deep Learning (Andrew W. Trask) and Neural Networks and Deep Learning (Michael Nielsen) 2. I'll probably be off-point here, but maybe The Book of Why (Judea Pearl) could be interesting reading for you. FloydHub has a great article about this topic on their blog: https://blog.floydhub.com/best-deep-learning-books-updated-f... (https://blog.floydhub.com/best-deep-learning-books-updated-for-2019/).

Seems like 'Deep Learning' [0] might suit for your first type of book. For the second type of book, may I suggest 'The Book of Why' by Judea Pearl. It isn't focused specifically on deep learning, but it is focused philosophical and cross disciplinary applications of statistical techniques. disclaimer: I haven't really dug in to deep learning, so I'll wager there may be great resources I'm completely unaware of. [0] 'Deep Learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville, MIT Press, https://www.deeplearningbook.org/