Deep Learning For Coders With Fastai Pytorch Ai Applications Without A Phd 1st Edition Jeremy Howard by Jeremy Howard, Sylvain Gugger 9781492045526, 1492045527 instant download after payment.

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