Jeremy Howard - Deep Learning for Coders With Fastai and Pytorch: Ai Applications Without a Phd

If you are looking for a guide that starts at the ground floor and takes you to the cutting edge of research, this is the book for you. Dont let those PhDs have all the fun you too can use deep learning to solve practical problems.

Hal Varian, Emeritus Professor, UC Berkeley; Chief Economist, Google

As artificial intelligence has moved into the era of deep learning, it behooves all of us to learn as much as possible about how it works. Deep Learning for Coders provides a terrific way to initiate that, even for the uninitiated, achieving the feat of simplifying what most of us would consider highly complex.

Eric Topol, Author, Deep Medicine; Professor, Scripps Research

Jeremy and Sylvain take you on an interactivein the most literal sense as each line of code can be run in a notebookjourney through the loss valleys and performance peaks of deep learning. Peppered with thoughtful anecdotes and practical intuitions from years of developing and teaching machine learning, the book strikes the rare balance of communicating deeply technical concepts in a conversational and light-hearted way. In a faithful translation of fast.ais award-winning online teaching philosophy, the book provides you with state-of-the-art practical tools and the real-world examples to put them to use. Whether youre a beginner or a veteran, this book will fast-track your deep learning journey and take you to new heightsand depths.

Sebastian Ruder, Research Scientist, Deepmind

Jeremy Howard and Sylvain Gugger have authored a bravura of a book that successfully bridges the AI domain with the rest of the world. This work is a singularly substantive and insightful yet absolutely relatable primer on deep learning for anyone who is interested in this domain: a lodestar book amongst many in this genre.

Anthony Chang, Chief Intelligence and Innovation Officer, Childrens Hospital of Orange County

How can I get deep learning without getting bogged down? How can I quickly learn the concepts, craft, and tricks-of-the-trade using examples and code? Right here. Dont miss the new locus classicus for hands-on deep learning.

Oren Etzioni, Professor, University of Washington; CEO, Allen Institute for AI

This book is a rare gemthe product of carefully crafted and highly effective teaching, iterated and refined over several years resulting in thousands of happy students. Im one of them. fast.ai changed my life in a wonderful way, and Im convinced that they can do the same for you.

Jason Antic, Creator, DeOldify

Deep Learning for Coders is an incredible resource. The book wastes no time and teaches how to use deep learning effectively in the first few chapters. It then covers the inner workings of ML models and frameworks in a thorough but accessible fashion, which will allow you to understand and build upon them. I wish there was a book like this when I started learning ML, it is an instant classic!

Emmanuel Ameisen, Author, Building Machine Learning Powered Applications

Deep Learning is for everyone, as we see in Chapter 1, Section 1 of this book, and while other books may make similar claims, this book delivers on the claim. The authors have extensive knowledge of the field but are able to describe it in a way that is perfectly suited for a reader with experience in programming but not in machine learning. The book shows examples first, and only covers theory in the context of concrete examples. For most people, this is the best way to learn.The book does an impressive job of covering the key applications of deep learning in computer vision, natural language processing, and tabular data processing, but also covers key topics like data ethics that some other books miss. Altogether, this is one of the best sources for a programmer to become proficient in deep learning.

Peter Norvig, Director of Research, Google

Gugger and Howard have created an ideal resource for anyone who has ever done even a little bit of coding. This book, and the fast.ai courses that go with it, simply and practically demystify deep learning using a hands-on approach, with pre-written code that you can explore and re-use. No more slogging through theorems and proofs about abstract concepts. In Chapter 1 you will build your first deep learning model, and by the end of the book you will know how to read and understand the Methods section of any deep learning paper.

Curtis Langlotz, Director, Center for Artificial Intelligence in Medicine and Imaging, Stanford University

This book demystifies the blackest of black boxes: deep learning. It enables quick code experimentations with a complete python notebook. It also dives into the ethical implication of artificial intelligence, and shows how to avoid it from becoming dystopian.

Guillaume Chaslot, Fellow, Mozilla

As a pianist turned OpenAI researcher, Im often asked for advice on getting into Deep Learning, and I always point to fastai. This book manages the seemingly impossibleits a friendly guide to a complicated subject, and yet its full of cutting-edge gems that even advanced practitioners will love.

Christine Payne, Researcher, OpenAI

An extremely hands-on, accessible book to help anyone quickly get started on their deep learning project. Its a very clear, easy to follow and honest guide to practical deep learning. Helpful for beginners to executives/managers alike. The guide I wished I had years ago!

Carol Reiley, Founding President and Chair, Drive.ai

Jeremy and Sylvains expertise in deep learning, their practical approach to ML, and their many valuable open-source contributions have made then key figures in the PyTorch community. This book, which continues the work that they and the fast.ai community are doing to make ML more accessible, will greatly benefit the entire field of AI.

Jerome Pesenti, Vice President of AI, Facebook

Deep Learning is one of the most important technologies now, responsible for many amazing recent advances in AI. It used to be only for PhDs, but no longer! This book, based on a very popular fast.ai course, makes DL accessible to anyone with programming experience. This book teaches the whole game, with excellent hands-on examples and a companion interactive site. And PhDs will also learn a lot.

Gregory Piatetsky-Shapiro, President, KDnuggets

An extension of the fast.ai course that I have consistently recommended for years, this book by Jeremy and Sylvain, two of the best deep learning experts today, will take you from beginner to qualified practitioner in a matter of months. Finally, something positive has come out of 2020!

Louis Monier, Founder, Altavista; former Head of Airbnb AI Lab

We recommend this book! Deep Learning for Coders with fastai and PyTorch uses advanced frameworks to move quickly through concrete, real-world artificial intelligence or automation tasks. This leaves time to cover usually neglected topics, like safely taking models to production and a much-needed chapter on data ethics.

John Mount and Nina Zumel, Authors, Practical Data Science with R

This book is for Coders and does not require a PhD. Now, I do have a PhD and I am no coder, so why have I been asked to review this book? Well, to tell you how friggin awesome it really is!

Within a couple of pages from Chapter 1 youll figure out how to get a state-of-the-art network able to classify cat vs. dogs in 4 lines of code and less than 1 minute of computation. Then you land Chapter 2, which takes you from model to production, showing how you can serve a webapp in no time, without any HTML or JavaScript, without owning a server.