Top 5 resources for learning Genetic Algorithms with Python

Jeremy Kallowitz
June 20, 2020

Top 5 resources for learning Genetic Algorithms with Python

As machine learning and Al has evolved, Genetic Programming has developed as one of the most interesting aspects. It is based on computer programs being encoded as set of genes and further modified using an evolutionary algorithm.

Following are the top five resources for detailed learning of Genetic Algorithm:

1. Introduction to Genetic Algorithms

Category: Book  Author: Melanie Mitchell

What will you learn?

This book covers an in-detail description of the historical background, evolution and informative examples of the subject to help you start from the basic concepts. Coming in an easy language, it includes use cases of genetic algorithms for scientific models.

2. Genetic Algorithms

Category: Video tutorial   Presenter: Darrel Whitley, Professor of Computer Science Department at Colorado State University

What will you learn?

If you are looking for canonical aspect of genetic algorithm along with experimental forms, this video tutorial is the best source. Using hyperplane sampling, it illustrates a genetic search. It also discusses the parallel island model, as well as parallel cellular genetic algorithm.

3. A Field Guide to Genetic Programming

Category: Book  Author: Riccardo Poli Poli, William B. Langdon, Nicholas Freitag McPhee

What will you learn?

This book introduces the basics of genetic programming and moves towards the use cases of genetic programming covering patentable inventions and novel scientific discoveries. With a unique perspective on this technique, this book has been rated as the best for genetic algorithms.

4. The Algorithm Design Manual

Category: Book   Author: Steve Skiena

What will you learn?

This book comes with extensive material on how to solve various types of problems. This book is divided into two parts. The first part makes you learn the technique for the design of genetic algorithm and includes analysis of computer algorithms. The second part has 75 most important algorithmic problems to allow some practical implementation.

5. Learning Genetic Algorithm

Category: Video tutorial   Presenter: Patrick H. Winston, American Computer Scientist and Professor at MIT

What will you learn?

If you are looking to dig deep into the conceptual part of genetic algorithm, this video tutorial is a highly recommended source. The instructor has put forward three approaches: how population progress towards desirable traits, what are the ranks of fitness and how wide is the diversity.

Using cases and live examples, the explanation ensures you get the most out of it!

Where to learn?

While you’re searching for some other sources, we have already found some for you such as CBT Nuggets and Pluralsight. However, which one is better, CBT Nuggets or Pluralsight?

Pluralsight offers you a 10-day free trial for the course ‘Understanding Genetic Algorithm and Genetic Programming’. The course has an academic way of learning, staring from basics and ending up at complexities. By the end, you will be able to control processes and make decisions.

On the other hand, CBT Nuggets also comes with a free trial but with 3x higher prices. You might find the teaching style as unprofessional and knowledge can be a little vague.


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