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Hands-On Genetic Algorithms with Python

You're reading from   Hands-On Genetic Algorithms with Python Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems

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Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781838557744
Length 346 pages
Edition 1st Edition
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Author (1):
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Eyal Wirsansky Eyal Wirsansky
Author Profile Icon Eyal Wirsansky
Eyal Wirsansky
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Table of Contents (18) Chapters Close

Preface 1. Section 1: The Basics of Genetic Algorithms
2. An Introduction to Genetic Algorithms FREE CHAPTER 3. Understanding the Key Components of Genetic Algorithms 4. Section 2: Solving Problems with Genetic Algorithms
5. Using the DEAP Framework 6. Combinatorial Optimization 7. Constraint Satisfaction 8. Optimizing Continuous Functions 9. Section 3: Artificial Intelligence Applications of Genetic Algorithms
10. Enhancing Machine Learning Models Using Feature Selection 11. Hyperparameter Tuning of Machine Learning Models 12. Architecture Optimization of Deep Learning Networks 13. Reinforcement Learning with Genetic Algorithms 14. Section 4: Related Technologies
15. Genetic Image Reconstruction 16. Other Evolutionary and Bio-Inspired Computation Techniques 17. Other Books You May Enjoy

Artificial neural networks and deep learning

Neural networks are among the most commonly used models in machine learning and were inspired by the structure of the human brain. The basic building blocks of these networks are nodes, or neurons, which are based on the biological neuron cell, as depicted in the following diagram:

Biological neuron model
Source: https://pixabay.com/vectors/neuron-nerve-cell-axon-dendrite-296581/

The neuron cell's dendrites, which are surrounding the cell body on the left-hand side of the preceding diagram, are used as inputs from multiple similar cells, while the long axon, coming out of the cell body, serves as output and can be connected to multiple other cells.

This structure is mimicked by the artificial model called the perceptron, illustrated as follows:

Artificial neuron model – the perceptron

The perceptron calculates the output...

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