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Hands-On Machine Learning with TensorFlow.js

You're reading from   Hands-On Machine Learning with TensorFlow.js A guide to building ML applications integrated with web technology using the TensorFlow.js library

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781838821739
Length 296 pages
Edition 1st Edition
Languages
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Author (1):
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Kai Sasaki Kai Sasaki
Author Profile Icon Kai Sasaki
Kai Sasaki
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: The Rationale of Machine Learning and the Usage of TensorFlow.js
2. Machine Learning for the Web FREE CHAPTER 3. Importing Pretrained Models into TensorFlow.js 4. TensorFlow.js Ecosystem 5. Section 2: Real-World Applications of TensorFlow.js
6. Polynomial Regression 7. Classification with Logistic Regression 8. Unsupervised Learning 9. Sequential Data Analysis 10. Dimensionality Reduction 11. Solving the Markov Decision Process 12. Section 3: Productionizing Machine Learning Applications with TensorFlow.js
13. Deploying Machine Learning Applications 14. Tuning Applications to Achieve High Performance 15. Future Work Around TensorFlow.js 16. Other Books You May Enjoy

Pose detection with ML5.js

ML5.js is a widely used high-level machine learning framework running on top of TensorFlow.js. It is designed to make machine learning accessible to a broad audience, such as students and artists. Those who are not familiar with machine learning tend to be only interested in the output of the algorithm, not the internal details of the algorithm. They are likely to want to write an efficient application without having to care too much about the optimization of the algorithm. ML5.js achieves good performance by using TensorFlow.js internally while providing an intuitive interface to developers.

As well as TensorFlow.js, ML5.js is distributed on the CDN, unpkg. Technically, you do not need to install anything in your application, you just need the following code:

<!DOCTYPE html> 
<html lang="en">
<head>
<title&gt...
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