web01.fireside.fm Tue, 28 Apr 2026 23:21:54 -0500 Fireside (https://fireside.fm) Pipeline Conversations - Episodes Tagged with β€œEducation” https://podcast.zenml.io/tags/education Wed, 12 Oct 2022 07:30:00 +0200 Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML. en-us episodic MLOps and LLMOps, from the trenches ZenML GmbH Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML. no machine-learning, machinelearning, mlops, deeplearning, ai, artificialintelligence, artificial-intelligence, technology, tech, mlops, llmops ZenML GmbH podcast@zenml.io The Full Stack with Charles Frye https://podcast.zenml.io/full-stack-charles-frye 4e698579-cdee-4f8f-ba34-4bca304129c2 Wed, 12 Oct 2022 07:30:00 +0200 ZenML GmbH full 2 ZenML GmbH 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. 57:05 no 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. Naturally, we get into education for practitioners as well as the things that Charles has seen in his own prior background working on production use cases. We also discuss the ways that tooling to support education as well as productive machine learning can and is being improved. Special Guest: Charles Frye. mlops, machine-learning, data-science, ai, artificial-intelligence, education, deep-learning 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.

Naturally, we get into education for practitioners as well as the things that Charles has seen in his own prior background working on production use cases. We also discuss the ways that tooling to support education as well as productive machine learning can and is being improved.

Special Guest: Charles Frye.

Links:

]]> 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.

Naturally, we get into education for practitioners as well as the things that Charles has seen in his own prior background working on production use cases. We also discuss the ways that tooling to support education as well as productive machine learning can and is being improved.

Special Guest: Charles Frye.

Links:

]]> Educating the next generation with Goku Mohandas https://podcast.zenml.io/goku-mohandas-made-with-ml 11960a13-d427-400c-8105-382ac76bc27f Thu, 29 Sep 2022 09:00:00 +0200 ZenML GmbH full 2 ZenML GmbH 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. 1:08:43 no In today's conversation, I'm speaking with Goku Mohandas, founder and creator of the amazing online resource MadeWithML (https://madewithml.com/). Goku has a bunch of practical experience, from working with Apple to a startup in the oncology space and much more. In this conversation we continued to unpack the theme of education in ML, the challenges when it comes to working across the full stack of ML applications, and what he's seen work in his experience working on MadeWithML (https://madewithml.com/). We also discuss some of the patterns he's seen in the production stacks he's seen in his experience consulting with various ML teams as well as where he sees room for improvement in the abstractions that we all rely on to do our work. Goku has generously agreed to be an external judge for our Month of MLOps competition that starts on October 10. If you haven't signed up yet, or want to learn more, please visit zenml.io/competition (https://zenml.io/competition). Special Guest: Goku Mohandas. mlops, machine-learning, data-science, ai, artificial-intelligence, infrastructure, education, medicine 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.

In this conversation we continued to unpack the theme of education in ML, the challenges when it comes to working across the full stack of ML applications, and what he's seen work in his experience working on MadeWithML.

We also discuss some of the patterns he's seen in the production stacks he's seen in his experience consulting with various ML teams as well as where he sees room for improvement in the abstractions that we all rely on to do our work.

Goku has generously agreed to be an external judge for our Month of MLOps competition that starts on October 10. If you haven't signed up yet, or want to learn more, please visit zenml.io/competition.

Special Guest: Goku Mohandas.

Links:

]]> 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.

In this conversation we continued to unpack the theme of education in ML, the challenges when it comes to working across the full stack of ML applications, and what he's seen work in his experience working on MadeWithML.

We also discuss some of the patterns he's seen in the production stacks he's seen in his experience consulting with various ML teams as well as where he sees room for improvement in the abstractions that we all rely on to do our work.

Goku has generously agreed to be an external judge for our Month of MLOps competition that starts on October 10. If you haven't signed up yet, or want to learn more, please visit zenml.io/competition.

Special Guest: Goku Mohandas.

Links:

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