Introduction to Machine Learning for the Sciences
by Titus Neupert, et al.
Publisher: arXiv.org 2021
Number of pages: 80
Description:
This is an introductory machine learning course specifically developed with STEM students in mind, written by the theoretical Condensed Matter Theory group at the University of Zurich and the Quantum Matter and AI group at the Delft University of Technology. We discuss supervised, unsupervised, and reinforcement learning.
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(4.1MB, PDF)
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