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Hands-On Genetic Algorithms with Python

You're reading from   Hands-On Genetic Algorithms with Python Apply genetic algorithms to solve real-world AI and machine learning problems

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781805123798
Length 418 pages
Edition 2nd 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 (24) Chapters Close

Preface 1. Part 1: The Basics of Genetic Algorithms
2. Chapter 1: An Introduction to Genetic Algorithms FREE CHAPTER 3. Chapter 2: Understanding the Key Components of Genetic Algorithms 4. Part 2: Solving Problems with Genetic Algorithms
5. Chapter 3: Using the DEAP Framework 6. Chapter 4: Combinatorial Optimization 7. Chapter 5: Constraint Satisfaction 8. Chapter 6: Optimizing Continuous Functions 9. Part 3: Artificial Intelligence Applications of Genetic Algorithms
10. Chapter 7: Enhancing Machine Learning Models Using Feature Selection 11. Chapter 8: Hyperparameter Tuning of Machine Learning Models 12. Chapter 9: Architecture Optimization of Deep Learning Networks 13. Chapter 10: Reinforcement Learning with Genetic Algorithms 14. Chapter 11: Natural Language Processing 15. Chapter 12: Explainable AI, Causality, and Counterfactuals with Genetic Algorithms 16. Part 4: Enhancing Performance with Concurrency and Cloud Strategies
17. Chapter 13: Accelerating Genetic Algorithms – the Power of Concurrency 18. Chapter 14: Beyond Local Resources – Scaling Genetic Algorithms in the Cloud 19. Part 5: Related Technologies
20. Chapter 15: Evolutionary Image Reconstruction with Genetic Algorithms 21. Chapter 16: Other Evolutionary and Bio-Inspired Computation Techniques 22. Index 23. Other Books You May Enjoy

ANNs and DL

Inspired by the structure of the human brain, NNs are among the most commonly used models in machine learning (ML). 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:

Figure 9.1: Biological neuron model

Figure 9.1: Biological neuron model

Source: https://simple.wikipedia.org/wiki/Neuron#/media/File:Neuron.svg by Dhp1080

The neuron cell’s dendrites, which surround 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 via its terminals.

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

Figure 9.2: Artificial neuron model – the perceptron

Figure 9.2: Artificial neuron model – the perceptron

The perceptron calculates the output by multiplying each of the input values by a certain...

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