The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

What's Next for Fast.ai? w/ Jeremy Howard - #421

Oct 21, 2020

Join Jeremy Howard, the founder of Fast.ai and author of 'Deep Learning for Coders,' as he dives into the evolution of AI education. He discusses Fast.ai's advancements and the importance of hands-on tools for aspiring data scientists. Howard reflects on the current state of deep learning and the growing demand for AI skills. The conversation also touches on the significance of community in learning and collaborations, as well as the challenges of promoting awareness during the COVID-19 pandemic. It's an insightful look into the future of machine learning!

01:01:19

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Episode guests

Jeremy Howard

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Episode notes

Intro

5min

The Evolution of Fast.ai and AI Education

23min

The Evolution of NBDev and MBDev

9min

Dynamics of Python and Self-Supervised Learning

11min

Celebrating Course Success

6min

The Importance of Community in Building Supportive Learning Environments

3min

Reflections on Advocacy and Community During COVID-19

4min

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.

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