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Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
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.
Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. Youâll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.
Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. Youâll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.
Product details
Publisher : O'Reilly Media; 1st edition (August 25, 2020)
Language : English
Paperback : 621 pages
ISBN-10 : 1492045527
ISBN-13 : 978-1492045526
Item Weight : 2.05 pounds
Dimensions : 6.9 x 1.1 x 9.1 inches
Best Sellers Rank: #137,567 in Books (See Top 100 in Books)
#19 in Machine Theory (Books)
#36 in Computer Neural Networks
#120 in Python Programming
Customer Reviews: 4.7
527 ratings
Publisher : O'Reilly Media; 1st edition (August 25, 2020)
Language : English
Paperback : 621 pages
ISBN-10 : 1492045527
ISBN-13 : 978-1492045526
Item Weight : 2.05 pounds
Dimensions : 6.9 x 1.1 x 9.1 inches
Best Sellers Rank: #137,567 in Books (See Top 100 in Books)
#19 in Machine Theory (Books)
#36 in Computer Neural Networks
#120 in Python Programming
Customer Reviews: 4.7
527 ratings
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