Machine Learning for Materials Research 2024

9AM – 4:30PM daily

Bootcamp (Days 1-4)

Four days of lectures and hands-on exercises covering a range of data analysis topics from introduction to python and data pre-processing to advanced machine learning analysis techniques. Example topics include:

• Identifying important features in complex/high dimensional data
• Visualizing high dimensional data to facilitate user analysis.
• Identifying the 'descriptors' that best predict variance in functional properties.
• Quantifying similarities between materials using complex/high dimensional data
• Identifying the most informative experiment to perform next.

Hands-on exercises will include practical use of machine learning tools on real materials experimental data (scalar values, spectra, micrographs, etc.)

Scientists will also demonstrate how they performed recently published research, from loading and preprocessing data to analyzing and visualizing results, all in Jupyter notebooks.

If you are a student (graduate, undergraduate, or high school), write to us first at MLMR@umd.edu, so we can send you a student discount code BEFORE you register. Write to us also for an academic discount code if you work at an academic institution (university, etc.) BEFORE you register.

The course registration will include all the course material (presentations slides in pdf files, jupyter notebook links, and recorded zoom lectures of the entire camp). As the camp start date approaches, we will be posting starting course material on the canvas website.