Compilation of notebooks dedicated to optimization processes in deep learning. Focus is on super-convergence, cyclical learning rates, lookahead, rectified Adam, and Adam methods.
https://www.slideshare.net/StefanKhn4/the-machinery-behind-deep-learning
https://arxiv.org/pdf/1708.07120.pdf
https://arxiv.org/abs/1506.01186
https://arxiv.org/abs/1907.08610
https://arxiv.org/pdf/1908.03265.pdf
https://arxiv.org/abs/1412.6980
This is a fork from an open-source project developed by another user. The project is now maintained by Skyworkin.
Compilation of notebooks dedicated to optimization processes in deep learning. Focus is on super-convergence, cyclical learning rates, lookahead, rectified Adam, and Adam methods.
GNU General Public License v3.0