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Deep Learning By Example

You're reading from Deep Learning By Example

Product type Book

Published in Feb 2018

Publisher Packt

ISBN-13 9781788399906

Pages 450 pages

Edition 1st Edition

Languages

Concepts

Table of Contents (18) Chapters

Preface

1. Data Science - A Birds' Eye View

2. Data Modeling in Action - The Titanic Example

3. Feature Engineering and Model Complexity – The Titanic Example Revisited

4. Get Up and Running with TensorFlow

5. TensorFlow in Action - Some Basic Examples

6. Deep Feed-forward Neural Networks - Implementing Digit Classification

7. Introduction to Convolutional Neural Networks

8. Object Detection – CIFAR-10 Example

9. Object Detection – Transfer Learning with CNNs

10. Recurrent-Type Neural Networks - Language Modeling

11. Representation Learning - Implementing Word Embeddings

12. Neural Sentiment Analysis

13. Autoencoders – Feature Extraction and Denoising

14. Generative Adversarial Networks

15. Face Generation and Handling Missing Labels

16. Implementing Fish Recognition

Code for fish recognition

17. Other Books You May Enjoy

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Summary

In this chapter, we covered the installation process for Ubuntu and Mac, gave an overview of the TensorFlow programming model, and explained the different types of simple nodes that could be used for building complex operations and how to get output from TensorFlow using a session object. Also, we covered TensorBoard and why it will helpful for debugging and analyzing complex deep learning applications.

Next, we will go through a basic explanation of neural networks and the intuition behind having multilayer neural networks. We will also cover some basic examples of TensorFlow and demonstrate how it could be used for regression and classification problems.

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