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Deep Learning Quick Reference

You're reading from   Deep Learning Quick Reference Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788837996
Length 272 pages
Edition 1st Edition
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Author (1):
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Mike Bernico Mike Bernico
Author Profile Icon Mike Bernico
Mike Bernico
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Table of Contents (15) Chapters Close

Preface 1. The Building Blocks of Deep Learning FREE CHAPTER 2. Using Deep Learning to Solve Regression Problems 3. Monitoring Network Training Using TensorBoard 4. Using Deep Learning to Solve Binary Classification Problems 5. Using Keras to Solve Multiclass Classification Problems 6. Hyperparameter Optimization 7. Training a CNN from Scratch 8. Transfer Learning with Pretrained CNNs 9. Training an RNN from scratch 10. Training LSTMs with Word Embeddings from Scratch 11. Training Seq2Seq Models 12. Using Deep Reinforcement Learning 13. Generative Adversarial Networks 14. Other Books You May Enjoy

Summary

In this chapter, we talked about how to install, configure, and use TensorBoard. We talked about how to use TensorBoard to compare models visually by inspecting their loss functions throughout each epoch in TensorBoard's SCALARS section. We then looked at visualizing the network structure using TensorsBoard's GRAPHS section. Finally, we showed you how to use TensorBoard for troubleshooting by looking at histograms.

In the next chapter, we will look how to use Keras and TensorFlow to solve binary classification problems, expanding our deep learning bag of tricks.

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