Data Science for Materials - a Collection of Open Resources for Education
Author: Logan Ward
Date Uploaded: 2024-11-01
Content Type(s): lecture and notebooks
Content Length: 1hr
Content Audience: graduate-level chemistry
Content Topics: fingerprints, descriptors, and QSPR
A brief introduction to a field with 30 years of history: the use of “machine learning” in chemistry. (Quotes emphasize that the studies we’ll take about often predate modern notions of machine learning) Discusses how data about molecules are represented for computers and how they are encoded for statistical learning algorithms. Many of the techniques used in chemoinformatics are extremely useful in materials engineering, and this lecture is intend to help you know a few of the basic ones.
The lecture is designed to cover theoretical aspects then the notebooks illustrate how to implement them with modern software packages.