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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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TensorBoard – visualizing learning

The computations you'll use TensorFlow for—such as training a massive deep neural network—can be complex and confusing, and its corresponding computational graph will be complex as well. To make it easier to understand, debug, and optimize TensorFlow programs, the TensorFlow team have included a suite of visualization tools called TensorBoard, which is a suite of web applications that can run through your browser. TensorBoard can be used to visualize your TensorFlow graph, plot quantitative metrics about the execution of your graph, and show additional data such as images that pass through it. When TensorBoard is fully configured, it looks like this:

To understand how TensorBoard works, we are going to build a computational graph which will act as a classifier for the MNIST dataset, which is a dataset of handwritten...

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