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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

Training a recommender system on a small curated dataset

You may recall that Chapter 1, Getting Started with fastai, described applications supported by fastai to cover four types of datasets: tabular, text, recommender systems, and images. In Chapter 2, Exploring and Cleaning Up Data with fastai, you saw sections on examining tabular datasets, text datasets, and image datasets.

You may have wondered why there wasn't a section on examining recommender system datasets. The reason is that the data ingestion process for recommender systems in fastai is identical to the process for tabular datasets, as you will see in this section. While the ingestion process for recommender systems in fastai is identical to the ingestion process for tabular datasets, fastai does provide model training details that are specifically intended for recommender systems.

In this section, we will go through the process of training a recommender system on a curated dataset to learn how to train recommender...

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