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TensorFlow Machine Learning Projects

You're reading from   TensorFlow Machine Learning Projects Build 13 real-world projects with advanced numerical computations using the Python ecosystem

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789132212
Length 322 pages
Edition 1st Edition
Languages
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Authors (2):
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Ankit Jain Ankit Jain
Author Profile Icon Ankit Jain
Ankit Jain
Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
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Toc

Table of Contents (17) Chapters Close

Preface 1. Overview of TensorFlow and Machine Learning FREE CHAPTER 2. Using Machine Learning to Detect Exoplanets in Outer Space 3. Sentiment Analysis in Your Browser Using TensorFlow.js 4. Digit Classification Using TensorFlow Lite 5. Speech to Text and Topic Extraction Using NLP 6. Predicting Stock Prices using Gaussian Process Regression 7. Credit Card Fraud Detection using Autoencoders 8. Generating Uncertainty in Traffic Signs Classifier Using Bayesian Neural Networks 9. Generating Matching Shoe Bags from Shoe Images Using DiscoGANs 10. Classifying Clothing Images using Capsule Networks 11. Making Quality Product Recommendations Using TensorFlow 12. Object Detection at a Large Scale with TensorFlow 13. Generating Book Scripts Using LSTMs 14. Playing Pacman Using Deep Reinforcement Learning 15. What is Next? 16. Other Books You May Enjoy

Summary

In this chapter, we learned what reinforcement learning is. Reinforcement learning is an advanced technique that you will find is often used to solve complex problems. We learned about OpenAI Gym, a framework that provides an environment for simulating many popular games in order to implement and practice reinforcement learning algorithms. We touched on deep reinforcement learning concepts, and we encourage you to explore books (mentioned in the further reading) specifically written about reinforcement learning to learn deeply about the theories and concepts.

We learned how to play the PacMan game in OpenAI Gym. We implemented DQN and used it to learn to play the PacMan game. We only used an MLP network to keep things simple, but, for complex examples, you may end up using complex CNN, RNN, or Sequence-to-Sequence models.

In the next chapter, we shall learn about...

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