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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

What is Next?

Congratulations on making it this far. So far, have learned to implement a variety of cutting-edge AI algorithms in TensorFlow and built cool projects on the side. Specifically, we have built projects on reinforcement learning, Bayesian neural networks, capsule networks, and Generative Adversarial Networks (GANs), among others. We have also learned about several modules of TensorFlow, including TensorFlow.js, TensorFlow Lite, and TensorFlow Probability, among others. This surely deserves a pat on the back and a well-earned rest.

Before we go out to play, there are a few more things that we should consider reading about before we are prime-time ready to deploy these cutting edge techniques in production. As we will realize in this chapter, there is more to deploying a machine learning model in production than just implementing the latest research paper in AI...

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