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Hands-on Machine Learning with JavaScript

You're reading from   Hands-on Machine Learning with JavaScript Solve complex computational web problems using machine learning

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788998246
Length 356 pages
Edition 1st Edition
Languages
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Author (1):
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Burak Kanber Burak Kanber
Author Profile Icon Burak Kanber
Burak Kanber
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Table of Contents (14) Chapters Close

Preface 1. Exploring the Potential of JavaScript FREE CHAPTER 2. Data Exploration 3. Tour of Machine Learning Algorithms 4. Grouping with Clustering Algorithms 5. Classification Algorithms 6. Association Rule Algorithms 7. Forecasting with Regression Algorithms 8. Artificial Neural Network Algorithms 9. Deep Neural Networks 10. Natural Language Processing in Practice 11. Using Machine Learning in Real-Time Applications 12. Choosing the Best Algorithm for Your Application 13. Other Books You May Enjoy

Conceptual overview of neural networks

ANNs have been around almost as long as computers have, and indeed were originally constructed out of electrical hardware. One of the first ANNs was developed in the 1970s to adaptively filter echoes out of phone line transmissions. Despite their initial early success, ANNs waned in popularity until the mid-1980s, when the backpropagation training algorithm was popularized.

ANNs are modeled on our understanding of biological brains. An ANN contains many neurons that connect to one another. The manner, structure, and organization of these neuronal connections is called the topology (or shape) of the network. Each individual neuron is a simple construct: it accepts several numerical input values and outputs a single numerical value, which may in turn be transmitted to several other neurons. The following is a simple, conceptual example of a...

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