MDI 450LEC - Machine Learning in Materials Design

This course covers the machine learning topics essential for sequential materials design. Case studies will be used as examples, with the goal being to create materials with targeted properties. The course begins with an outline of important probability and statistical topics, including random vectors, conditional probabilities. We then turn to Bayesian statistics, prior and posterior distributions. We then focus on machine learning models for regression. The final component of the course focuses on decision-making algorithms, and Bayesian experimental design.

Credits: 3

Grading
Graded (GRD)

Typically Offered:
Spring

Requisites:
Pre-Requisites: MDI 404