Genetic Algorithms in Elixir

Overview

Join the experts, Sean Moriarity and Bruce Tate, as they guide you through the intricate world of genetic algorithms using the Elixir programming language. This event is perfect for programmers and AI enthusiasts eager to enhance their problem-solving skills.

Whether you're just getting started or looking to apply these concepts to real-world scenarios, this talk will provide valuable insights and practical knowledge.

Hosted on YouTube, this session is categorized under Artificial Intelligence Courses and Conference Talks, making it a valuable resource for anyone looking to expand their understanding in these areas.

Syllabus

• Introduction to Genetic Algorithms
Overview of Genetic Algorithms
Key Concepts: Chromosomes, Genes, Fitness Function
Natural Evolution vs. Genetic Algorithms
• Getting Started with Elixir
Introduction to Elixir
Setting Up the Development Environment
Basic Syntax and Functional Programming Concepts
• Implementing Genetic Algorithms in Elixir
Representing Solutions in Elixir
Designing the Fitness Function
Selection Mechanisms
Crossover Operators
Mutation Techniques
Elixir-specific Libraries and Tools for Genetic Algorithms
• Developing Problem-Solving Techniques
Solving Optimization Problems
Case Study: Traveling Salesman Problem
Adapting Genetic Algorithms to Different Problem Domains
• Real-World Applications
Genetic Algorithms in Machine Learning
Evolving Neural Networks
Industrial and Business Applications
• Advanced Topics in Genetic Algorithms
Hybrid Genetic Algorithms
Parallel and Distributed Genetic Algorithms with Elixir
Fine-Tuning and Parameter Optimization
• Project: Building a Genetic Algorithm Solution
Defining a Real-World Problem
Designing and Implementing a Solution in Elixir
Testing and Evaluation
• Course Summary and Future Directions
Review of Key Concepts
Exploring Further Applications
Additional Resources and Next Steps in Elixir and AI

---

Subjects

Conference Talks