Deep Learning for Coders with fastai and PyTorch : AI Applications Without a PhD (includes 224 Colour Pages)

Author 1: Sylvain Gugger

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9789385889202
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    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. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.

    • Train models in computer vision, natural language processing, tabular data, and collaborative filtering
    • Learn the latest deep learning techniques that matter most in practice
    • Improve accuracy, speed, and reliability by understanding how deep learning models work
    • Discover how to turn your models into web applications
    • Implement deep learning algorithms from scratch
    • Consider the ethical implications of your work
    • Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
    Books
    Author
    Jeremy Howard
    Author 1
    Sylvain Gugger
    Binding
    Paperback
    Condition Type
    New
    Country Origin
    India
    Edition
    First
    Gift Wrap
    N
    Leadtime to ship in days (default)
    ships in 1-2 days
    Pages
    624
    Publication Date
    16/10/2020
    Publisher
    Shroff/O'Reilly
    Year
    2020
    Dimensions
    Dimensions (W x H x D)
    7 x 9 x 1.3 inch

    Table of Contents (9789385889202_toc.pdf, 343 Kb) [Download]

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