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Mastering Predictive Analytics with R

You're reading from   Mastering Predictive Analytics with R Master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781783982806
Length 414 pages
Edition 1st Edition
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Toc

Table of Contents (13) Chapters Close

Preface 1. Gearing Up for Predictive Modeling 2. Linear Regression FREE CHAPTER 3. Logistic Regression 4. Neural Networks 5. Support Vector Machines 6. Tree-based Methods 7. Ensemble Methods 8. Probabilistic Graphical Models 9. Time Series Analysis 10. Topic Modeling 11. Recommendation Systems Index

The biological neuron


Neural network models draw their analogy from the organization of neurons in the human brain, and for this reason they are also often referred to as artificial neural networks (ANNs) to distinguish them from their biological counterparts. The key parallel is that a single biological neuron acts as a simple computational unit, but when a large number of these are combined together, the result is an extremely powerful and massively distributed processing machine capable of complex learning, known more commonly as the human brain. To get an idea of how neurons are connected in the brain, the following image shows a simplified picture of a human neural cell:

In a nutshell, we can think of a human neuron as a computational unit that takes in a series of parallel electrical signal inputs known as synaptic neurotransmitters coming in from the dendrites. The dendrites transmit signal chemicals to the soma or body of the neuron in response to the received synaptic neurotransmitters...

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