Fundamentals of Deep Learning

Regular price €76.99
A01=Joe Papa
A01=Nikhil Buduma
A01=Nithin Buduma
AI Deep learning machine learning artificial intelligence pytorch tensorflow neural networks convolutional networks transformers recurrent neural networks generative models interpretability reinforcement learning
Author_Joe Papa
Author_Nikhil Buduma
Author_Nithin Buduma
Category=UYQM
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction

Product details

  • ISBN 9781492082187
  • Dimensions: 178 x 232mm
  • Publication Date: 31 May 2022
  • Publisher: O'Reilly Media
  • Publication City/Country: US
  • Product Form: Paperback
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We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception that has powered our push toward self-driving vehicles, the ability to defeat human experts at a variety of difficult games including Go and Starcraft, and even generate essays with shockingly coherent prose. But deciphering these breakthroughs often takes a Ph.D. education in machine learning and mathematics. This updated second edition describes the intuition behind these innovations without the jargon and complexity. By the end of this book, Python-proficient programmers, software engineering professionals, and computer science majors will be able to re-implement these breakthroughs on their own and reason about them with a level of sophistication that rivals some of the best in the field. New chapters cover recent advancements in the fields of generative modeling and interpretability. Code examples throughout the book are updated to TensorFlow 2 and PyTorch 1.4.