IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz - GitHub - dynamicslab/databook_python: IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
Deep Learning Fundamentals -- Code material and exercises - GitHub - Lightning-AI/dl-fundamentals: Deep Learning Fundamentals -- Code material and exercises
D. Galvin. (2014)cite arxiv:1406.7872Comment: Notes prepared to accompany a series of tutorial lectures given by the author at the 1st Lake Michigan Workshop on Combinatorics and Graph Theory, Western Michigan University, March 15--16 2014.
Z. Wang, and S. Ji. (2018)cite arxiv:1808.08931Comment: The original version was accepted by KDD2018. Code is publicly available at https://github.com/divelab/dilated.
M. Finzi, K. Wang, and A. Wilson. (2020)cite arxiv:2010.13581Comment: NeurIPS 2020. Code available at https://github.com/mfinzi/constrained-hamiltonian-neural-networks.
T. Miyato, S. Maeda, M. Koyama, and S. Ishii. (2017)cite arxiv:1704.03976Comment: To be appeared in IEEE Transactions on Pattern Analysis and Machine Intelligence.