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You're reading from Advanced Deep Learning with Python Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch

Product type Paperback

Published in Dec 2019

Publisher Packt

ISBN-13 9781789956177

Length 468 pages

Edition 1st Edition

Languages

Python

Tools

PyTorch

Concepts

Deep Learning

Author (1):

Ivan Vasilev

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Table of Contents (17) Chapters

Preface

1. Section 1: Core Concepts FREE CHAPTER

2. The Nuts and Bolts of Neural Networks

3. Section 2: Computer Vision

4. Understanding Convolutional Networks

5. Advanced Convolutional Networks

6. Object Detection and Image Segmentation

7. Generative Models

8. Section 3: Natural Language and Sequence Processing

9. Language Modeling

10. Understanding Recurrent Networks

11. Sequence-to-Sequence Models and Attention

12. Section 4: A Look to the Future

13. Emerging Neural Network Designs

14. Meta Learning

15. Deep Learning for Autonomous Vehicles

16. Other Books You May Enjoy

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Section 4: A Look to the Future

In this section, we'll discuss some recent DL techniques that have not reached widespread adoption yet, but are nevertheless promising.

This section contains the following chapters:

Chapter 9, Emerging Neural Network Designs
Chapter 10, Meta Learning
Chapter 11, Deep Learning for Autonomous Vehicles

The rest of the chapter is locked

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Authors (1)

Vasilev

Ivan Vasilev started working on the first open source Java deep learning library with GPU support in 2013. The library was acquired by a German company, with whom he continued its development. He has also worked as a machine learning engineer and researcher in medical image classification and segmentation with deep neural networks. Since 2017, he has focused on financial machine learning. He co-founded an algorithmic trading company, where he's the lead engineer. He holds an MSc in artificial intelligence from Sofia University St. Kliment Ohridski and has written two previous books on the same topic.

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