Reproducible Machine Learning Results By Default

Last Updated on August 16, 2020

It is good practice to have reproducible outcomes in software projects. It might even be standard practice by now, I hope it is.

You can take any developer off the street and they should be able to follow your process to check out the code base from revision control and make a build of the software ready to use. Even better if you have a procedure for setting up an environment and for releasing the software to users/operational environments.

It is the tools and the process make the outcome reproducible. In this post you will learn that it is just as important to make the outcomes of your machine learning projects reproducible and that practitioners and academics in the field of machine learning struggle with this.

As a programmer and a developer you already have the tools and the process to leap ahead, if you have the discipline.

Reproducible Computational Research

Reproducible Computational Research
Photo credit ZEISS Microscopy, some rights reserved

Reproducibility of Results in Computational Sciences

Reproducibility of
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