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

Product type Paperback

Published in Nov 2018

Publisher Packt

ISBN-13 9781789132212

Length 322 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Authors (2):

Ankit Jain

Dr. Amita Kapoor

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Table of Contents (17) Chapters

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

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Decision tree-based ensembles in TensorFlow

In this chapter, we shall use the gradient boosted trees and random forest implementation as pre-made estimators in TensorFlow from the Google TensorFlow team. Let us learn the details of their implementation in the upcoming sections.

TensorForest Estimator

TensorForest is a highly scalable implementation of random forests built by combining a variety of online HoeffdingTree algorithms with the extremely randomized approach.

Google published the details of the TensorForest implementation in the following paper: TensorForest: Scalable Random Forests on TensorFlow by Thomas Colthurst, D. Sculley, Gibert Hendry, Zack Nado, presented at Machine Learning...

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Authors (2)

Jain

Ankit Jain holds a bachelor's degree in computer science and engineering. He has 6 years, experience in designing and architecting solutions for the big data domain and has been involved with several complex engagements. His technical strengths include Hadoop, Storm, S4, HBase, Hive, Sqoop, Flume, Elasticsearch, machine learning, Kafka, Spring, Java, and J2EE. He also shares his thoughts on his personal blog. You can follow him on Twitter at @mynameisanky. He spends most of his time reading books and playing with different technologies. When not at work, he spends time with his family and friends watching movies and playing games.

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Amita Kapoor

Amita Kapoor, a seasoned expert in Artificial Intelligence, serves as the Chief Artificial Intelligence Officer at TIPZ AI, bringing over 25 years of experience in AI, data science, and neuroscience. Her consultancy, NePeur, stands testament to her leadership in applying AI across diverse industries, enhancing operational efficiency and business intelligence. Amita is also a devoted board member of Neuromatch Academy, where she plays a crucial role in making neuroscience and deep learning education accessible to all. Holding a PhD from the University of Delhi, she has dedicated her career to education, authoring numerous articles and papers, and creating impactful online classes. Her significant contributions extend to pioneering projects in intelligent vehicle fleet management, home surveillance through AI-powered face detection, and robust data anonymization solutions. Connect with Amita on LinkedIn.

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