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Deep Learning with fastai Cookbook

You're reading from Deep Learning with fastai Cookbook Leverage the easy-to-use fastai framework to unlock the power of deep learning

Product type Paperback

Published in Sep 2021

Publisher Packt

ISBN-13 9781800208100

Length 340 pages

Edition 1st Edition

Languages

Python

Tools

fastai

Concepts

Deep Learning

Author (1):

Mark Ryan

View More author details

Table of Contents (10) Chapters

Preface

1. Chapter 1: Getting Started with fastai

2. Chapter 2: Exploring and Cleaning Up Data with fastai FREE CHAPTER

3. Chapter 3: Training Models with Tabular Data

4. Chapter 4: Training Models with Text Data

5. Chapter 5: Training Recommender Systems

6. Chapter 6: Training Models with Visual Data

7. Chapter 7: Deployment and Model Maintenance

8. Chapter 8: Extended fastai and Deployment Features

9. Other Books You May Enjoy

Technical requirements

Ensure that you have completed the setup sections from Chapter 1, Getting Started with fastai, and have a working Gradient instance or Colab setup. The recipes described in this chapter assume that you are using Gradient. Ensure that you have cloned the repository for the book, https://github.com/PacktPublishing/Deep-Learning-with-fastai-Cookbook, and have access to the ch5 folder. This folder contains the code samples described in this chapter.

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Authors (1)

Ryan

Ryan

Mark Ryan is a machine learning practitioner and technology manager who is passionate about delivering end-to-end deep learning applications that solve real-world problems. Mark has worked on deep learning projects that incorporate a variety of related technologies, including Rasa chatbots, web applications, and messenger platforms. As a strong believer in democratizing technology, Mark advocates for Keras and fastai as accessible frameworks that open up deep learning to non-specialists. Mark has a degree in computer science from the University of Waterloo and a Master of Science degree in computer science from the University of Toronto.

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