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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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Toc

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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

absolute value 97

activation function 68, 70

linear activation function 70

Rectified Linear Unit activation function 70

Adadelta 83

Adagrad 83

Adam 83

AdaMax 83

ADE20K 300

AlexNet 133

AlexNet custom model

creating, from scratch 135, 136

evaluating 137

training 136, 137

AlexNet pre-trained model

evaluating, from Model Zoo 140

loading, from Model Zoo 139, 140

Area Under the Curve (AUC) 147

Atrous Spatial Pyramid Pooling (ASPP) 170

attention 184

attention heads 185

cross-attention head 186

self-attention head 186

Automatic Mixed Precision (AMP) 271

applying, for inference 303

enabling, for training optimization 271

using 313

average pooling layer 130

B

Back-Propagation Through Time (BPTT) 180

Bag-Of-Words...

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