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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 a decision tree is and two broad classes of creating ensembles from the decision trees. The ensembles we took a look at were random forests and gradient boosting trees.

We also learned about the Kepler dataset from Kaggle competitions. We used the Kepler dataset to build an exoplanet detection model using TensorFlow's prebuilt estimator for gradient boosting trees known as the BoostedTreesClassifier. The BoostedTreesClassifier estimator is part of the machine learning toolkit recently released by the TensorFlow team. As for now, the TensorFlow team is working on releasing prebuilt estimators based on support vector machine (SVM) and extreme random forests as part of the tf.estimators API.

In the next chapter, we shall learn how to use TensorFlow in the browser using the TensorFlow.js API for sentiment analysis.

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