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Tutorial DIAMOND GA 2026

This tutorial offers a series of educational notebooks designed to introduce the application of machine learning to materials science.

Through practical examples, the notebooks progressively introduce different approaches, ranging from data analysis and exploration to prediction, the discovery of causal relationships, and Bayesian optimization.

Prerequisites

To complete this tutorial, you will need one of the following:

  • Apptainer installed (installation guide)
  • OR have Docker installed
  • OR have Python 3.10+ installed with uv and Graphviz (more information on how to install them is provided in the tutorial).

This training session was organized ahead of the DIAMOND 2026 general meeting in Lyon.

The training program was developed by Ahmed AMRANI and co-supervised by Ahmed AMRANI, Jean-Philippe POLI and Léo ORVEILLON.

The full content, along with instructions on how to run it, is available in the tutorial’s repository, and the guide walks through it step by step: links below.

Guide: ML Training

Follow the tutorial step by step

GitLab: ML Training

Access the notebooks and instructions