Course DescriptionPyTorch Lightning reduces the engineering boilerplate and resources required to implement state-of-the-art AI. Organizing PyTorch code with Lightning enables seamless training on multiple GPUs, TPUs, CPUs as well as the use of difficult to implement best practices such as model sharding, 16-bit precision, and more, without any code changes. In this talk, we will start with a general overview of Deep Learning and then transition into practical Lightning examples to demonstrate how to train Deep Learning models with less boilerplate.
Two GiHub Repos
Jirka Borovec- He has worked in machine learning and data science for several years. He holds a Ph.D. in Medical Imaging. Nowadays, he is focusing on Computer vision and Deep learning. He has also developed several open-source Python packages, moreover, he is a core contributor of PyTorch-lightning and actively participating in other well-known projects such as `scikit-image` and `auto-sklearn`.