Genetic Algorithms in Elixir
Gain insights into building genetic algorithm frameworks in Elixir. Learn about statistics, genealogy tracking, and solving practical problems with customizable genetic algorithm frameworks.
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What You'll Learn
- Learn about the basics of Genetic Algorithms in Elixir.
- Learn how to design the framework for using Genetic Algorithms.
- Explore the processes of selection, crossover, mutation and reinsertion.
- Analyze the performance of the Genetic Algorithms by benching and profiling them.
- Explore the different ways of visualizing Genetic Algorithms along with testing and type checking your code.
Learning Roadmap
1.
Introduction
Introduction
2.
Writing Your First Genetic Algorithm
Writing Your First Genetic Algorithm
3.
Breaking Down Genetic Algorithms
Breaking Down Genetic Algorithms
6 Lessons
6 Lessons
4.
Encoding Problems and Solutions
Encoding Problems and Solutions
6 Lessons
6 Lessons
5.
Evaluating Solutions and Populations
Evaluating Solutions and Populations
6 Lessons
6 Lessons
6.
Selecting the Best
Selecting the Best
5 Lessons
5 Lessons
7.
Generating New Solutions
Generating New Solutions
7 Lessons
7 Lessons
8.
Preventing Premature Convergence
Preventing Premature Convergence
5 Lessons
5 Lessons
9.
Replacing and Transitioning
Replacing and Transitioning
5 Lessons
5 Lessons
10.
Tracking Genetic Algorithms
Tracking Genetic Algorithms
6 Lessons
6 Lessons
11.
Visualizing the Results
Visualizing the Results
4 Lessons
4 Lessons
12.
Optimizing Your Algorithms
Optimizing Your Algorithms
7 Lessons
7 Lessons
13.
Writing Tests and Code Quality
Writing Tests and Code Quality
4 Lessons
4 Lessons
14.
Moving Forward
Moving Forward
4 Lessons
4 Lessons
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