Fundamentals of Deep Learning
Designing Next-Generation Machine Intelligence Algorithms
by Nikhil Buduma · first published 2017
33% recommend67% neutral
With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, alon
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The new O'Reilly book "Fundamentals of Deep Learning" by Nikhil Buduma (available on Safari for a while now) is good at the fundamentals- very clearly explained, nice diagrams. It it relatively close to the path of my Neural Networks classes (although those…
on “Free “Deep Learning” Textbook by Goodfellow and Bengio Now Finished” ↗…Python" - was afraid it'd be too basic, but not really. Enjoyed it a lot. - "Think Complexity" - about algorithm complexity, data structures, etc. Great read. - "Python Data Science Handbook" - meh. - "Fundamentals of Deep Learning" - good intro. Helped me solidify some concepts from Andrew Ng's ML course - "Deep Learning" - by Goodfellow and Bengio. Just started, but really liking it. [STARTUPS] (all excellent; in order) - "The…
on “Ask HN: Books you read in 2016?” ↗Deep Learning | Boston | Nick L | njl@mit.edu | http://nicklocascio.com Founded + lectured MIT's deep learning course (6.S191), contributing writer to O'Reilly's Fundamentals of Deep Learning book, deep learning consultant for Fortune 500. Down to chat about and give advice about anything in the machine and deep learning space! Interested to hear what you're working on! :)
on “Ask HN: Who's mentoring?” ↗