Joining us today on How AI Happens is Sebastian Raschka, Lead AI educator at GRID.ai and Assistant Professor of Statistics at the University of Wisconsin-Madison. Sebastian fills us in on the coursework he’s creating in his role at GRID.ai, and we find out what can be attributed to the crossover of machine learning in academia and the private sector. We speculate on the pros and cons of the commodification of deep learning models and which machine learning framework is better: PyTorch or TensorFlow.
Key Points From This Episode:
Stream the full episode below.
Tweetables:“In academia, the focus is more on understanding how deep learning works… On the other hand, in the industry, there are use cases of machine learning.” — @rasbt “Often it is hard to formulate answers as a human to complex questions.” — @rasbt “In my experience, deep learning can be very powerful but you need a lot of data to make it work well.” — @rasbt “In , I tried to provide a resource that is a hybrid between more theoretical books and more applied books.” — @rasbt “Why I like PyTorch is that it gives me the readability flexibility to customize things.” — @rasbt Links Mentioned in Today’s Episode:Sebastian RaschkaSebastian Raschka on TwitterGRID.aiMachine Learning with PyTorch and Scikit-Learn