Preface

fastai is an easy-to-use deep learning framework built on top of PyTorch that lets you rapidly create complete deep learning solutions with as few as 10 lines of code. Both of the predominant low-level deep learning frameworks today (TensorFlow and PyTorch) require a lot of code, even for straightforward applications. In contrast, fastai handles the messy details for you and lets you focus on applying deep learning to actually solve problems.

We will start by summarizing the value of fastai and showing a simple "hello world" deep learning application with fastai. Then, we will describe how to use fastai for each of the four application areas that the framework explicitly supports: tabular data, text data (NLP), recommender systems, and vision data. You will work through a series of practical examples that illustrate how to create real-world applications of each type. After that, you will learn how to deploy fastai models. For example, you will learn how to create a simple web application that predicts what object is depicted in an image. Finally, we will wrap up with an overview of the advanced features of fastai.

By the end of this book, you will be able to create your own deep learning applications using fastai. You'll know how to use fastai to prepare raw datasets, explore datasets, train deep learning models, and deploy trained models.