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Updated 27 Aug
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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.

74 lessons
1 project
25h 30min
Created by The Pragmatic Programmers
Genetic Algorithms in Elixir
What's included
  • 74 lessons across 14 modules
  • 16 quizzes with instant feedback
  • 1 project in preconfigured environments
  • AI Tutor on every lesson
Who wrote it
The Pragmatic Programmers
We create timely, practical books and learning resources on classic and cutting-edge topics to help you practice your craft and accelerate your career.

Andy Hunt and Dave Thomas founded The Pragmatic Programmers, LLC., with a simple goal: to improve the lives of professional developers. We create timely, practical books and other learning resources on classic and cutting-edge topics to help you learn and practice your craft and accelerate your career. We are not a giant, faceless, greed-soaked corporation. We’re a small group of experienced professionals committed to helping make corporate software development—and your life—easier.

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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

74 Lessons16 Quizzes

1.

Introduction

Introduction

Get familiar with Genetic Algorithms in Elixir, their applications, and Elixir's advantages.

3.

Breaking Down Genetic Algorithms

Breaking Down Genetic Algorithms

6 Lessons

6 Lessons

Work your way through the fundamental structure and processes of genetic algorithms in Elixir.

4.

Encoding Problems and Solutions

Encoding Problems and Solutions

6 Lessons

6 Lessons

Grasp the fundamentals of enhancing genetic algorithms with Elixir's structs and behaviours.

5.

Evaluating Solutions and Populations

Evaluating Solutions and Populations

6 Lessons

6 Lessons

Take a closer look at optimizing cargo loads, penalty functions, termination criteria, and crafting fitness functions.

6.

Selecting the Best

Selecting the Best

5 Lessons

5 Lessons

Incorporate various selection strategies in genetic algorithms to balance diversity and fitness.

7.

Generating New Solutions

Generating New Solutions

7 Lessons

7 Lessons

Piece together the parts of effective crossover strategies to enhance genetic algorithm solutions.

8.

Preventing Premature Convergence

Preventing Premature Convergence

5 Lessons

5 Lessons

Break down methods to prevent premature convergence using mutation strategies and diverse techniques.

9.

Replacing and Transitioning

Replacing and Transitioning

5 Lessons

5 Lessons

Unpack the core of genetic algorithms for class scheduling, reinsertion, and population management strategies.

10.

Tracking Genetic Algorithms

Tracking Genetic Algorithms

6 Lessons

6 Lessons

Examine genetic algorithm simulations and track evolution statistics, genealogy trees, and adaptive traits.

11.

Visualizing the Results

Visualizing the Results

4 Lessons

4 Lessons

Apply your skills to visualizing genetic algorithm results and creating AI agents for Atari games.

12.

Optimizing Your Algorithms

Optimizing Your Algorithms

7 Lessons

7 Lessons

Take a closer look at optimizing genetic algorithms through benchmarking, profiling, and parallelization in Elixir.

13.

Writing Tests and Code Quality

Writing Tests and Code Quality

4 Lessons

4 Lessons

Tackle code testing, property tests, code cleanup, and type specifications for reliable Elixir frameworks.

14.

Moving Forward

Moving Forward

4 Lessons

4 Lessons

Build on the role of genetic algorithms in AI, real-life applications, neural networks, and advanced exploration.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Fahim Ul HaqGenetic Algorithms in ElixirFounder & CEO
About this course
WHY I WROTE THIS COURSE
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 genetic algorithms. By the end, you’ll have a full-featured, customizable framework complete with statistics, genealogy tracking, and more, and you’ll have learned everything you need to solve practical problems with genetic algorithms.
ABOUT THE AUTHOR

The Pragmatic Programmers

We create timely, practical books and learning resources on classic and cutting-edge topics to help you practice your craft and accelerate your career.

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