Deep Learning for Coders with fastai and PyTorch

This guide demonstrates that programmers who are comfortable with Python can achieve impressive results in deep learning with minimal code and little math background. With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications, authors Jeremy Howard and Sylvain Gugger 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. With insights from PyTorch cofounder, Soumith Chintala, and coverage of computer vision, natural language processing, tabular data, and collaborative filtering, this book is a comprehensive resource for anyone looking to improve their deep learning skills.