Dynamics of Python and Self-Supervised Learning

In this special #TWIMLfest episode of the podcast, we’re joined by Jeremy Howard, Founder of Fast.ai.

In our conversation with Jeremy, we discuss his career path, including his journey through the consulting world and how those experiences led him down the path to ML education, his thoughts on the current state of the machine learning adoption cycle, and if we’re at maximum capacity for deep learning use and capability.

Of course, we dig into the newest version of the fast.ai framework and course, the reception of Jeremy’s book ‘Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD,’ and what’s missing from the machine learning education landscape. If you’ve missed our previous conversations with Jeremy, I encourage you to check them out here and here.

The complete show notes for this episode can be found at https://twimlai.com/go/421.