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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

Who is this book for?

This book is ideal for Data Scientists, Machine Learning Engineers, and Developers who want to work with Apache MXNet for building fast, scalable deep learning solutions. The reader is expected to have a good understanding of Python programming and a working environment with Python 3.7+. A good theoretical understanding of mathematics for deep learning will be beneficial.

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