This deep dive is all about neural networks - training them using best practices, debugging them and maximizing their performance using cutting edge research.
“This guide is designated to anybody with basic programming knowledge or a computer science background interested in becoming a Research Scientist with on Deep Learning and NLP”.
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
P. Heinisch, A. Dulny, A. Krause, and A. Hotho. Workshop on Neuro-Explicit AI and Expert-Informed Machine Learning for Engineering and Physical Sciences at the ECML PKDD 2023, (2023)cite arxiv:2306.14511.