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Deep Learning with MXNet Cookbook

You're reading from  Deep Learning with MXNet Cookbook

Product type Book
Published in Dec 2023
Publisher Packt
ISBN-13 9781800569607
Pages 370 pages
Edition 1st Edition
Languages
Author (1):
Andrés P. Torres Andrés P. Torres
Profile icon Andrés P. Torres

Table of Contents (12) Chapters

Preface 1. Chapter 1: Up and Running with MXNet 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

Technical requirements

Apart from the technical requirements specified in the Preface, the following technical requirements apply to this chapter:

  • Ensure that you have completed Recipe 1, Installing MXNet, Gluon, GluonCV and GluonNLP, from Chapter 1, Up and Running with MXNet
  • Ensure that you have completed Recipe 4, Toy dataset for text classification: Load, manage, and visualize a spam email dataset, from Chapter 2, Working with MXNet and Visualizing Datasets: Gluon and DataLoader

The code for this chapter can be found at the following GitHub URL: https://github.com/PacktPublishing/Deep-Learning-with-MXNet-Cookbook/tree/main/ch06

Furthermore, you can access each recipe directly from Google Colab; for example, use the following link for the first recipe of this chapter: https://colab.research.google.com/github/PacktPublishing/Deep-Learning-with-MXNet-Cookbook/blob/main/ch06/6_1_Introducing_NLP_Networks.ipynb.

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