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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

"Hello world" for fastai – creating a model for MNIST

Now that you have set up your environment for fastai, it's time to run through an example. In this section, you will go through the process of creating a simple deep learning model trained on the MNIST dataset. This dataset consists of images of handwritten digits. The goal of the trained model is to predict the digit given an image. For example, we want the trained model to predict that the following digits are 6, 3, 9, and 6:

Figure 1.30 – Sample handwritten digits from the MNIST dataset

We won't be covering every detail of the fastai solution for MNIST in this section, but we will be running a complete example that demonstrates one of the key values of fastai—getting a powerful deep learning result with only a few lines of code. This example should also whet your appetite for the more advanced fastai examples that are coming in subsequent chapters.

Getting ready...

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