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    <title>Pipeline Conversations - Episodes Tagged with “Medicine”</title>
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    <pubDate>Thu, 29 Sep 2022 09:00:00 +0200</pubDate>
    <description>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.
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    <itunes:subtitle>MLOps and LLMOps, from the trenches</itunes:subtitle>
    <itunes:author>ZenML GmbH</itunes:author>
    <itunes:summary>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.
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  <title>Educating the next generation with Goku Mohandas</title>
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  <pubDate>Thu, 29 Sep 2022 09:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
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  <itunes:subtitle>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.</itunes:subtitle>
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  <description>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.
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  <itunes:keywords>mlops, machine-learning, data-science, ai, artificial-intelligence, infrastructure, education, medicine</itunes:keywords>
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    <![CDATA[<p>In today&#39;s conversation, I&#39;m speaking with Goku Mohandas, founder and creator of the amazing online resource <a href="https://madewithml.com/" rel="nofollow">MadeWithML</a>. Goku has a bunch of practical experience, from working with Apple to a startup in the oncology space and much more.</p>

<p>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&#39;s seen work in his experience working on <a href="https://madewithml.com/" rel="nofollow">MadeWithML</a>.</p>

<p>We also discuss some of the patterns he&#39;s seen in the production stacks he&#39;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.</p>

<p>Goku has generously agreed to be an external judge for our Month of MLOps competition that starts on October 10. If you haven&#39;t signed up yet, or want to learn more, please visit <a href="https://zenml.io/competition" rel="nofollow">zenml.io/competition</a>.</p><p>Special Guest: Goku Mohandas.</p><p>Links:</p><ul><li><a title="Goku on LinkedIn" rel="nofollow" href="https://www.linkedin.com/in/goku/">Goku on LinkedIn</a></li><li><a title="GokuMohandas (Goku Mohandas) on GitHub" rel="nofollow" href="https://github.com/GokuMohandas">GokuMohandas (Goku Mohandas) on GitHub</a></li><li><a title="Home - Made With ML" rel="nofollow" href="https://madewithml.com/">Home - Made With ML</a></li><li><a title="Goku Mohandas (@GokuMohandas) / Twitter" rel="nofollow" href="https://twitter.com/GokuMohandas">Goku Mohandas (@GokuMohandas) / Twitter</a></li><li><a title="Made With ML (@MadeWithML) / Twitter" rel="nofollow" href="https://twitter.com/MadeWithML">Made With ML (@MadeWithML) / Twitter</a></li></ul>]]>
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    <![CDATA[<p>In today&#39;s conversation, I&#39;m speaking with Goku Mohandas, founder and creator of the amazing online resource <a href="https://madewithml.com/" rel="nofollow">MadeWithML</a>. Goku has a bunch of practical experience, from working with Apple to a startup in the oncology space and much more.</p>

<p>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&#39;s seen work in his experience working on <a href="https://madewithml.com/" rel="nofollow">MadeWithML</a>.</p>

<p>We also discuss some of the patterns he&#39;s seen in the production stacks he&#39;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.</p>

<p>Goku has generously agreed to be an external judge for our Month of MLOps competition that starts on October 10. If you haven&#39;t signed up yet, or want to learn more, please visit <a href="https://zenml.io/competition" rel="nofollow">zenml.io/competition</a>.</p><p>Special Guest: Goku Mohandas.</p><p>Links:</p><ul><li><a title="Goku on LinkedIn" rel="nofollow" href="https://www.linkedin.com/in/goku/">Goku on LinkedIn</a></li><li><a title="GokuMohandas (Goku Mohandas) on GitHub" rel="nofollow" href="https://github.com/GokuMohandas">GokuMohandas (Goku Mohandas) on GitHub</a></li><li><a title="Home - Made With ML" rel="nofollow" href="https://madewithml.com/">Home - Made With ML</a></li><li><a title="Goku Mohandas (@GokuMohandas) / Twitter" rel="nofollow" href="https://twitter.com/GokuMohandas">Goku Mohandas (@GokuMohandas) / Twitter</a></li><li><a title="Made With ML (@MadeWithML) / Twitter" rel="nofollow" href="https://twitter.com/MadeWithML">Made With ML (@MadeWithML) / Twitter</a></li></ul>]]>
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