Pipeline Conversations
MLOps and LLMOps, from the trenches
Displaying 8 items of Pipeline Conversations with the tag "artificial-intelligence".
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Questioning MLOps with Lak Lakshmanan
October 27th, 2022 | Season 2 | 53 mins 2 secs
ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops, scale
This week I spoke with Lak Lakhshmanan, who worked for years at Google on ML and AI projects and products at a senior level and he also brings years of experience working on meteorology and other scientific projects previously.
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The Full Stack with Charles Frye
October 12th, 2022 | Season 2 | 57 mins 5 secs
ai, artificial-intelligence, data-science, deep-learning, education, machine-learning, mlops
This week I spoke with Charles Frye. Not only has Charles volunteered to be a judge on our Month of MLOps competition happening right now, he's part of the core team working on the Full Stack Deep Learning course.
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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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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.