Deep Learning for Coders with fastai and PyTorch (includes 224 Colour Pages) (Paperback, Jeremy Howard, Sylvain Gugger) (Paperback, Jeremy Howard, Sylvain Gugger)
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Deep Learning for Coders with fastai and PyTorch (includes 224 Colour Pages) (Paperback, Jeremy Howard, Sylvain Gugger) (Paperback, Jeremy Howard, Sylvain Gugger)
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.
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Publication Year
2020 2020-10-16
Contributors
Author Info
Jeremy Howard is the President and Chief Scientist at Kaggle. Previously, he founded FastMail (sold to Opera Software) and Optimal Decisions (sold to ChoicePoint - now called LexisNexis Risk Solutions). Prior to that he worked in management consulting, at McKinsey & Company and A.T. Kearney. Sylvain is a former teacher and a Research Scientist at fast.ai, with a focus on making deep learning more accessible by designing and improving techniques that allow models to train fast on limited resources.