Jeff Heaton

Welcome to Heaton Research, the site that contains my projects, books, and blog. My name is Jeff Heaton, I am a data scientist, indy publisher, and adjunct instructor at Washington University. My interests include machine learning, feature engineering, and real world applications of these topics. I am known for AI books, Kickstarter projects, YouTube Videos and open source projects. I use the programming languages Python, R, Java, and C#. My blog can be found here.

I am most active on GitHub and YouTube, and at times Twitter. If would like to keep up to date on my projects, just follow me:

Upcoming Presentations

  • Prepare.AI - April 9, 2019, St. Louis, MO at Washington University School of Medicine: Presenting on Deep Learning with Electronic Health Records (EHR)
  • PAW: Deep Learning World - June 18, 2019, Las Vegas, NV. Presenting: "How Much Data is Enough for Deep Learning?"

Deep Learning Course @ WUSTL

I teach T81-558:Applications of Deep Neural Networks as an adjunct faculty member of Washington University in St. Louis. This is a hybrid course that combines classroom learning with Internet delivered videos. All material for this class can be found at the link provided. For more information on participating in this course outside of Washington University, click here.


I also have an interest in Artificial Life and created MergeLife is a family of cellular automata that I developed. Each member of this family is represented by a hexidecimal encoding, such
as E542-5F79-9341-F31E-6C6B-7F08-8773-7068 that represent a MergeLife update rule. The three patterns that you see above are three different MergeLife update rules. Other than a random starting grid, these update rules are
completly deterministic. MergeLife rules are discovered using a Genetic Algorithm. You can think of MergeLife as a utility to create entirely new Cellular Automata that are similar to Conway's Game of Life. Complete implementations of MergeLife in Java, Python, and JavaScript are provided on GitHub.