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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 covered the basics of sequence-to-sequence models, including how they work and how we can use them. Hopefully, we've shown you a powerful tool for machine translation, question-answering, and chat applications.

If you've made it this far, good job. You've seen quite a few applications of deep learning and you're finding yourself on the right of the bell curve toward the state-of-the-art in the application of deep neural networks.

In the next chapter, I'm going to show you an example of another advanced topic, deep reinforcement learning, or deep-Q learning, and show you how to implement your own deep-Q network.

Until then, sois détendu!

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