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MATLAB for Machine Learning

You're reading from  MATLAB for Machine Learning

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781788398435
Pages 382 pages
Edition 1st Edition
Languages
Authors (2):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
Pavan Kumar Kolluru Pavan Kumar Kolluru
Profile icon Pavan Kumar Kolluru
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Credits
Foreword
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with MATLAB Machine Learning 2. Importing and Organizing Data in MATLAB 3. From Data to Knowledge Discovery 4. Finding Relationships between Variables - Regression Techniques 5. Pattern Recognition through Classification Algorithms 6. Identifying Groups of Data Using Clustering Methods 7. Simulation of Human Thinking - Artificial Neural Networks 8. Improving the Performance of the Machine Learning Model - Dimensionality Reduction 9. Machine Learning in Practice

Basic elements of a neural network


The atomic computational unit of a neural network is the artificial neuron. It simulates several basic functions of the biological neuron, evaluates the intensity of each input, sums up the different inputs, and compares the result with an appropriate threshold. Finally, it determines what the output value is. The basic anatomy of the neuron is known and the main biochemical reactions that govern its activity have been identified. A neuron can be considered the elemental computational unit of the brain. In the human brain, about 100 different classes of neurons have been identified. The following figure shows the scheme of a single neuron:

Figure 7.5: Neural network scheme

The main feature of the neuron is to generate an electric potential propagating along the axon (neuron output) when electrical activity at the neuron body level exceeds a certain threshold. Neuron input is a set of fibers called dendrites; they are in contact with the axons of other neurons...

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