Deep Learning with fastai Cookbook
Deep Learning with fastai Cookbook
Language - English
Updated on Jan, 2023
About the Book
Book description
Harness the power of the easy-to-use, high-performance fastai framework to rapidly create complete deep learning solutions with few lines of code
Key Features
- Discover how to apply state-of-the-art deep learning techniques to real-world problems
- Build and train neural networks using the power and flexibility of the fastai framework
- Use deep learning to tackle problems such as image classification and text classification
Book Description
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 predominant low-level deep learning frameworks, 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.
The book begins by summarizing the value of fastai and showing you how to create a simple 'hello world' deep learning application with fastai. You'll then learn how to use fastai for all four application areas that the framework explicitly supports: tabular data, text data (NLP), recommender systems, and vision data. As you advance, you'll work through a series of practical examples that illustrate how to create real-world applications of each type. Next, you'll learn how to deploy fastai models, including creating a simple web application that predicts what object is depicted in an image. The book wraps up with an overview of the advanced features of fastai.
By the end of this fastai book, you'll be able to create your own deep learning applications using fastai. You'll also have learned how to use fastai to prepare raw datasets, explore datasets, train deep learning models, and deploy trained models.
What you will learn
- Prepare real-world raw datasets to train fastai deep learning models
- Train fastai deep learning models using text and tabular data
- Create recommender systems with fastai
- Find out how to assess whether fastai is a good fit for a given problem
- Deploy fastai deep learning models in web applications
- Train fastai deep learning models for image classification
Who this book is for
This book is for data scientists, machine learning developers, and deep learning enthusiasts looking to explore the fastai framework using a recipe-based approach. Working knowledge of the Python programming language and machine learning basics is strongly recommended to get the most out of this deep learning book.

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Author Details

Packt Publishing
Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals.
Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools.
As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.
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