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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

In this chapter, you will be running deployments on your local system, which requires having fastai installed on your local system. To run fastai locally, a Windows or Linux system is recommended, with Python installed. While fastai can be installed on macOS, you will save yourself a lot of headaches if you use a Windows or Linux system for your local installation of fastai.

Ensure that you have cloned the repo for the book at https://github.com/PacktPublishing/Deep-Learning-with-fastai-Cookbook and have access to the ch7 folder. This folder contains the code samples described in this chapter.

The rest of the chapter is locked

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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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