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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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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

Using Machine Learning to Detect Exoplanets in Outer Space

In this chapter, we shall learn how to detect exoplanets in outer space using ensemble methods that are based on decision trees.

Decision trees are a family of non-parametric supervised learning methods. In a decision tree algorithm, the data is divided into two partitions by using a simple rule. The rule is applied again and again to further partition the data, thus forming a tree of decisions.

Ensemble methods combine the learning from multiple learning algorithms to improve predictions and reduce errors. These ensembles are differentiated on the basis of what kind of learners they use and how they structure those learns in the ensemble.

The two most popular ensemble methods based on decision trees are known as gradient boosted trees and random forests. 

The following topics will be covered in this chapter:

  • What...
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