Pipeline Conversations
A Machine Learning Podcast by ZenML
Displaying Episode 11 - 19 of 19 in total of Pipeline Conversations with the tag “ai”.
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Educating the next generation with Goku Mohandas
September 29th, 2022 | Season 2 | 1 hr 8 mins
ai, artificial-intelligence, data-science, education, infrastructure, machine-learning, medicine, mlops
In today's conversation, I'm speaking with Goku Mohandas, founder and creator of the amazing online resource MadeWithML. Goku has a bunch of practical experience, from working with Apple to a startup in the oncology space and much more.
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ML Abstractions with Phil Howes
September 5th, 2022 | Season 2 | 54 mins 13 secs
ai, data-science, infrastructure, machine-learning, mlops, pipelines, platforms, tools
This week we dive into the abstractions that we're all trying to layer on top of the core ML processes and workflows. I spoke with Phil Howes, co-founder and chief scientist at BaseTen. BaseTen is a platform that allows data scientists to go from an initial model to an MVP web app quickly.
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Building MLOps Tools with Outerbounds
August 22nd, 2022 | Season 2 | 59 mins 43 secs
ai, data-science, infrastructure, machine-learning, mlops, pipelines, tools
This week I spoke with Savin Goyal and Hugo Bowne-Anderson from Outerbounds. They both work on leading, building and helping people put models into production through Metaflow, and I'm sure current users of ZenML will find this conversation interesting to hear how they think through the broader questions and engineering problems involved with MLOps.
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ML Engineering with Ben Wilson
June 8th, 2022 | Season 2 | 1 hr 4 mins
ai, data-science, infrastructure, machine-learning, mlops, pipelines, tools
Today, I'm extremely excited to present this conversation I had with Ben Wilson who works over at Databricks and who has also just released a new book called 'Machine Learning Engineering in Action'.
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Trustworthy ML with Kush Varshney
April 14th, 2022 | 39 mins 8 secs
ai, artificial-intelligence, bias, data-science, ethics, fairness, machine-learning
I enthusiastically read Kush Varshney's book when it was released for free to the world several months back. Trustworthy Machine Learning is a concise and clear overview of many of the ways that machine learning can go wrong, and so I was especially keen to get Kush on to talk more about his work and research.
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Open-Source MLOps with Matt Squire
March 31st, 2022 | 47 mins 41 secs
ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops, open-source
This week I spoke with Matt Squire, the CTO and co-founder of Fuzzy Labs, where they help partner organisations think through how best to productionise their machine learning workflows.
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Practical Production ML with Emmanuel Ameisen
March 17th, 2022 | 58 mins
ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops
This week I spoke with Emmanuel Ameisen, a data scientist and ML engineer currently based at Stripe. Emmanuel also wrote an excellent O'Reilly book called "Building Machine Learning Powered Applications", a book I find myself often returning to for inspiration and that I was pleased to get the chance to reread in preparation for our discussion.
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The Modern Data Stack with Tristan Zajonc
February 10th, 2022 | 59 mins 4 secs
ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops
This week I spoke with Tristan Zajonc, the CEO and cofounder of Continual, a company that provides an AI layer for enterprise companies or, as we'll get into in the podcast, the so-called 'modern data stack'.
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Neurosymbolic AI with Mohan Mahadevan
January 27th, 2022 | 58 mins 55 secs
ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops
Our guest this week was Mohan Mahadevan, a senior VP at Onfido, a machine-learning powered identity verification platform. He has previously worked at Amazon heading up a computer vision team working on robotics applications as well as for many years at KLA, a leading semiconductor hardware company. He holds a doctorate in theoretical physics from Colorado State University.