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

Exploring the FastAI Tooling Ecosystem with Hamel Husain - #532

Nov 1, 2021

Hamel Husain, a Staff Machine Learning Engineer at GitHub, has contributed to pivotal open-source projects like FastAI and nbdev. He shares insights from his journey through Silicon Valley and discusses the ML tooling gaps he encountered. The conversation highlights innovative tools like MBDev that integrate coding and documentation, while also exploring how FastAI enhances data science workflows. Hamel expresses excitement for future ML tools and the seamless automation capabilities of GitHub Actions, promising a more efficient coding experience.

39:38

Creator website

Episode guests

Hamel Husain

AI Chapters

Episode notes

Intro

2min

Navigating Machine Learning: From GitHub to FastAI

12min

Unlocking Efficient Coding with MBDev

18min

Leveraging Tools for Enhanced Data Science Workflows

3min

Simplifying Workflows with GitHub Actions

2min

Integration of Machine Learning Tools and Future Directions

3min

Today we’re joined by Hamel Husain, Staff Machine Learning Engineer at GitHub.

Over the last few years, Hamel has had the opportunity to work on some of the most popular open source projects in the ML world, including fast.ai, nbdev, fastpages, and fastcore, just to name a few. In our conversation with Hamel, we discuss his journey into Silicon Valley, and how he discovered that the ML tooling and infrastructure weren’t quite as advanced as he’d assumed, and how that led him to help build some of the foundational pieces of Airbnb’s Bighead Platform.

We also spend time exploring Hamel’s time working with Jeremy Howard and the team creating fast.ai, how nbdev came about, and how it plans to change the way practitioners interact with traditional jupyter notebooks. Finally, talk through a few more tools in the fast.ai ecosystem, fastpages, fastcore, how these tools interact with Github Actions, and the up and coming ML tools that Hamel is excited about.

The complete show notes for this episode can be found at twimlai.com/go/532.

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