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Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD
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About Deep Learning For Coders With Fastai And
Review "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. Don't 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 of Deep Medicine; Professor: Scripps Research "Jeremy and Sylvain take you on an interactive--in the most literal sense as each line of code can be run in a notebook--journey 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.ai's 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 you're a beginner or a veteran, this book will fast-track your deep learning journey and take you to new heights--and 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, Children's 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. Don't 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 gem- the product of carefully crafted and highly effective teaching, iterated and refined over several years resulting in thousands of happy students. I'm one of them. fast.ai changed my life in a wonderful way, and I'm convinced that they can do the same for you." -- Jason Antic, Creator of 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 of Building Machine Learning Powered Applications ""Deep Learning is for everyone" 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 c
