CH 610 Course Materials

These are the lecture notes for the Machine Learning in Chemistry course for Winter 2025. This course is intended for graduate students and advanced undergraduate students. Jupyter notebooks of in-class tutorials are available in the course GitHub repository. Homeworks, assignments, and test materials are confidential and will not be shared publicly.

Disclaimer: The reference books for each lecture are listed in the second slide of the lecture. Figures taken from the reference books are not explicitly cited. Citations may be missing for some other images I collected from Google. Please note that these images are copyrighted and I cannot authorize their use in any published material.

Topic 1 – Introduction

Topic 2 – Challenges in Machine Learning

Topic 3 – Regression

Topic 4 – Classification

Topic 5 – Decision Tree, Random Forest , Boosting

Topic 6 – Dimensionality Reduction

Topic 7 – Clustering

Topic 8 – Deep Learning

Advanced Topic 1 – Convolutional Neural Network

Advanced Topic 2 – Graph Neural Network

Advanced Topic 3 – Generative Machine Learning