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Deep Learning for Coders with Fastai and Pytorch: AI Applications Without a PhD

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Item specifics

Condition
New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Deep Learning for Coders with Fastai and Pytorch: AI Applications
ISBN
9781492045526
Subject Area
Computers
Publication Name
Deep Learning for Coders with Fastai and Pytorch : Ai Applications Without a Phd
Publisher
O'reilly Media, Incorporated
Item Length
9.2 in
Subject
Programming / General, Machine Theory, Image Processing, Computer Science, Neural Networks, Data Visualization, Programming Languages / Python
Publication Year
2020
Type
Textbook
Format
Trade Paperback
Language
English
Item Height
1.5 in
Author
Jeremy Howard, Sylvain Gugger
Item Weight
38.2 Oz
Item Width
7 in
Number of Pages
621 Pages

About this product

Product Information

Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks--including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively into deep learning theory so that by the end of the book you'll have a complete understanding of the math behind the library's functions.

Product Identifiers

Publisher
O'reilly Media, Incorporated
ISBN-10
1492045527
ISBN-13
9781492045526
eBay Product ID (ePID)
28038665481

Product Key Features

Number of Pages
621 Pages
Language
English
Publication Name
Deep Learning for Coders with Fastai and Pytorch : Ai Applications Without a Phd
Publication Year
2020
Subject
Programming / General, Machine Theory, Image Processing, Computer Science, Neural Networks, Data Visualization, Programming Languages / Python
Type
Textbook
Subject Area
Computers
Author
Jeremy Howard, Sylvain Gugger
Format
Trade Paperback

Dimensions

Item Height
1.5 in
Item Weight
38.2 Oz
Item Length
9.2 in
Item Width
7 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2022-278837
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.312
Lc Classification Number
Qa76.9.D343h69 2020

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Retrostar Music
James Billington
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United States
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