forgi86/dl-sysid-lyon2026
Material for the mini-course on Deep Learning for System Identification (Lyon 2026)
This project provides educational materials for engineers, researchers, and students interested in using deep learning to understand and model dynamic systems. It takes basic knowledge of Python and numerical tools as input and provides structured learning modules, code examples, and slides to teach system identification techniques using deep neural networks. The target audience includes control engineers, data scientists, and anyone working with time-series data to create predictive models.
Use this if you want to learn how to apply deep learning methods to analyze and build models from dynamic system data.
Not ideal if you are looking for a plug-and-play software tool for immediate system identification without hands-on learning.
Stars
9
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1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 27, 2026
Commits (30d)
0
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