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

Technical requirements

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

  • Ensure that you have completed the first recipe, Installing MXNet, Gluon, GluonCV and GluonNLP, from Chapter 1, Up and Running with MXNet.
  • Ensure that you have completed Chapter 5, Analyzing Images with Computer Vision, and Chapter 6, Understanding Text with Natural Language Processing.

The code for this chapter can be found at the following GitHub URL: https://github.com/PacktPublishing/Deep-Learning-with-MXNet-Cookbook/tree/main/ch07.

Furthermore, you can access each recipe directly from Google Colab; for example, the first recipe of this chapter can be found here: https://colab.research.google.com/github/PacktPublishing/Deep-Learning-with-MXNet-Cookbook/blob/main/ch07/7_1_Understanding_Transfer_Learning_and_Fine_Tuning.ipynb.

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