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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

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781800208100
Length 340 pages
Edition 1st Edition
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Author (1):
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Mark Ryan Mark Ryan
Author Profile Icon Mark Ryan
Mark Ryan
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Table of Contents (10) Chapters Close

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

Setting up JupyterLab environment in Gradient

Earlier in this chapter, we went through the steps to set up Gradient as an environment to explore fastai. With this set up, you get the standard Jupyter notebook environment that features a filesystem view and the ability to update notebooks, launch terminal windows, and perform basic operations such as uploading and downloading files from your local system. If you want a richer development environment, you can set up Gradient to use JupyterLab.

In addition to allowing you to maintain multiple views (for example, a terminal view along with several notebooks) within the same browser tab, JupyterLab also lets you take advantage of visual debuggers in the context of a notebook. In this section, we will go through the steps to set up Gradient so that you can use JupyterLab. Note that this recipe is optional—any example in this book that you can run in Gradient with JupyterLab will also work in vanilla Jupyter.

Getting ready

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