Deep Learning for Coders with Fastai and Pytorch : AI Applications Without a PhD (Paperback)

Gugger, Sylvain, Howard, Jeremy



Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away.

Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks--including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively into deep learning theory so that by the end of the book you'll have a complete understanding of the math behind the library's functions.





Sylvain is a former teacher and a Research Scientist at, with a focus on making deep learning more accessible by designing and improving techniques that allow models to train fast on limited resources.

Prior to this, Sylvain wrote several books covering the entire curriculum he was teaching in France (published at Éditions Dunod) until 2015 in CPGE. CPGE are a French specific two-year program whereby handpicked students who graduated high school follow an intense preparation before sitting for the competitive exam to enter the top engineering and business schools of the country. Sylvain taught computer science and mathematics in that program for seven years.

Sylvain is an alumni from École Normale Supérieure (Paris, France) where he studied mathematics and has a Master's Degree in mathematics from University Paris XI (Orsay, France).

Jeremy Howard is an entrepreneur, business strategist, developer, and educator. Jeremy is a founding researcher at, a research institute dedicated to making deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, a faculty member at Singularity University, and a Young Global Leader with the World Economic Forum.

Jeremy's most recent startup, Enlitic, was the first company to apply deep learning to medicine, and has been selected one of the world's top 50 smartest companies by MIT Tech Review two years running. He was previously the President and Chief Scientist of the data science platform Kaggle, where he was the top ranked participant in international machine learning competitions 2 years running. He was the founding CEO of two successful Australian startups (FastMail, and Optimal Decisions Group-purchased by Lexis-Nexis). Before that, he spent 8 years in management consulting, at McKinsey & Co, and AT Kearney. Jeremy has invested in, mentored, and advised many startups, and contributed to many open source projects.

He has many television and other video appearances, including as a regular guest on Australia's highest-rated breakfast news program, a popular talk on, and data science and web development tutorials and discussions.



在此之前,Sylvain撰寫了幾本書,涵蓋了他在法國教授的整個課程(由Éditions Dunod出版),直到2015年在CPGE教授。CPGE是法國特定的為期兩年的課程,被挑選的高中畢業生在參加進入該國頂尖工程和商學院的競爭性考試前,接受密集的準備。Sylvain在該計劃中教授計算機科學和數學,共七年。

Sylvain畢業於法國巴黎的École Normale Supérieure,主修數學,並擁有法國奧賽大學(Orsay)的數學碩士學位。

Jeremy Howard是一位企業家、商業策略師、開發者和教育家。Jeremy是fast.ai的創始研究員,該研究所致力於使深度學習更易於接觸。他還是舊金山大學的杰出研究科學家,是Singularity University的教職成員,也是世界經濟論壇的青年全球領袖。

Jeremy最近的創業公司Enlitic是第一家將深度學習應用於醫學領域的公司,連續兩年被MIT Tech Review評為全球最聰明的50家公司之一。他曾擔任數據科學平台Kaggle的總裁和首席科學家,在國際機器學習競賽中連續兩年排名第一。他還是兩家成功的澳大利亞初創公司(FastMail和Optimal Decisions Group,後被Lexis-Nexis收購)的創始人兼首席執行官。在此之前,他在麥肯錫和AT Kearney等管理咨詢公司擔任了8年的職位。Jeremy投資、指導和建議了許多初創公司,並為許多開源項目做出了貢獻。