What does the machine learning production stack of the future look like? Should we expect a thousand and one unique configurations, or will there be one deployment tool to rule them all? Our latest podcast guest, Noah Gift, gave us his thoughts on these questions and a whole lot more in our new episode of Pipeline Conversations.

Noah is the founder of Pragmatic A.I. Labs, where they produce videos, books and courses to support those hoping to get into the field. He also lectures at various universities in the United States and teaches online courses as well. From earlier in his career, Noah also has film credits in many major motion pictures for technical work, including Avatar, Spider-Man 3, and Superman Returns.

Practical MLOps is Noah’s latest book, co-written with Alfredo Deza. It covers a wide range of practical ways to work with machine learning models in production. The book takes a thoroughly hands-on approach — one honed through the experience that Noah has teaching, one would imagine — and it’s a useful way to get your hands dirty in a huge number of different ways. If you’re new to the field, there are dozens of small projects to try out at the end of each chapter.

Noah also shared his hard-won experiences from working to build up a sports social media startup, as well as his sense of what would be a good place to start as someone seeking to build up their own practical experience in MLOps. Check out out the full episode below or however you prefer to listen to podcasts!


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