This text is a practical, example-driven guide to introduce classical machine learning techniques using the scikit-learn library, designed for engineers with limited to no programming experience. This preface collects the essential housekeeping information for using this text.
A current PDF version of the text can be found here.
Videos of lectures associated with this text are available as a YouTube playlist here.
Playlist of videos associated with this text.
This project uses Python programmed through the Spyder IDE managed through the Anaconda platform. A video series that walks the practitioner through this combination of IDE and distribution manager is provided here.
Playlist of videos for learning how to program in Python using Spyder and Anaconda.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License [cc-by-sa 4.0].
Cite as
@Article{Downey2025MachineLearningEngineering,
author = {Downey, Austin {R.J.}},
title = {Machine Learning for Engineering Problem Solving: A Practical Example-driven Guide to Classical Techniques},
year = {2025},
month = jul,
doi = {10.31224/4909},
publisher = {Open Engineering Inc},
}