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Deep Learning with MXNet Cookbook

You're reading from   Deep Learning with MXNet Cookbook Discover an extensive collection of recipes for creating and implementing AI models on MXNet

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781800569607
Length 370 pages
Edition 1st Edition
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Author (1):
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Andrés P. Torres Andrés P. Torres
Author Profile Icon Andrés P. Torres
Andrés P. Torres
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Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Up and Running with MXNet FREE CHAPTER 2. Chapter 2: Working with MXNet and Visualizing Datasets – Gluon and DataLoader 3. Chapter 3: Solving Regression Problems 4. Chapter 4: Solving Classification Problems 5. Chapter 5: Analyzing Images with Computer Vision 6. Chapter 6: Understanding Text with Natural Language Processing 7. Chapter 7: Optimizing Models with Transfer Learning and Fine-Tuning 8. Chapter 8: Improving Training Performance with MXNet 9. Chapter 9: Improving Inference Performance with MXNet 10. Index 11. Other Books You May Enjoy

Classifying images with MXNet – GluonCV Model Zoo, AlexNet, and ResNet

MXNet provides a variety of tools to compose custom deep learning models. In this recipe, we will see how to use MXNet to build a model from scratch, train it, and use it to classify images from a dataset. We will also see that although this approach works fine, it is time-consuming.

Another option, and one of the highest value features that MXNet and GluonCV provide, is their Model Zoo. GluonCV Model Zoo is a set of pre-trained, ready-to-go models, for use with your own applications. We will see how to use Model Zoo with two very important models for image classification – AlexNet and ResNet.

In this recipe, we will analyze and compare these approaches to classify images on a reduced version of the Dogs vs. Cats dataset.

Getting ready

As with previous chapters, in this recipe, we will use a few matrix operations and linear algebra, but it will not be too difficult.

Furthermore, we will...

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