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Genetic Algorithms in Elixir

74 Lessons
16 Quizzes
52 Playgrounds
97 Illustrations

Takeaway Skills

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.

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.

Course Overview

This course has been designed to introduce you to a field of programming you might have never been exposed to. In this course, you’ll learn everything you need to know to start working with genetic algorithms. As you work through the course, you’ll build a framework for problems using ...

How You'll Learn

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Hands-on coding environments

You don’t get better at swimming by watching others. Coding is no different. Practice as you learn with live code environments inside your browser.

Faster than videos

Videos are holding you back. The average video tutorial is spoken at 150 words per minute, while you can read at 250. That‘s why our courses are text-based.

No set-up required

Start learning immediately instead of fiddling with SDKs and IDEs. It‘s all on the cloud.

Progress you can show

Built in assessments let you test your skills. Completion certificates let you show them off.

Course Contents

1. Introduction
2. Writing Your First Genetic Algorithm
3. Breaking Down Genetic Algorithms
4. Encoding Problems and Solutions
5. Evaluating Solutions and Populations
6. Selecting the Best
7. Generating New Solutions
8. Preventing Premature Convergence
9. Replacing and Transitioning
10. Tracking Genetic Algorithms
11. Visualizing the Results
12. Optimizing Your Algorithms
13. Writing Tests and Code Quality
14. Moving Forward

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