- eBook:Genetic Algorithms in Elixir: Solve Problems Using Evolution
- Author:Sean Moriarity
- Edition:1 edition
- Data:February 9, 2021
- Pages:244 pages
Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind.
Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications.
Open your eyes to a unique and powerful field - without having to learn a new language or framework.
What You Need:
You'll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.
2. Breaking Down Genetic Algorithms
3. Encoding Problems and Solutions
4. Evaluating Solutions and Populations
5. Selecting the Best
6. Generating New Solutions
7. Preventing Premature Convergence
8. Replacing and Transitioning
9. Tracking Genetic Algorithms
10. Visualizing the Results
11. Optimizing Your Algorithms
12. Writing Tests and Code Quality
13. Moving Forward
Download Genetic Algorithms in Elixir: Solve Problems Using Evolution PDF or ePUB format free