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    <fireside:genDate>Mon, 13 Apr 2026 12:27:21 -0500</fireside:genDate>
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    <title>Pipeline Conversations - Episodes Tagged with “Open Source”</title>
    <link>https://podcast.zenml.io/tags/open-source</link>
    <pubDate>Mon, 26 Sep 2022 14:00:00 +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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    <language>en-us</language>
    <itunes:type>episodic</itunes:type>
    <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.
</itunes:summary>
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    <itunes:explicit>no</itunes:explicit>
    <itunes:keywords>machine-learning, machinelearning, mlops, deeplearning, ai, artificialintelligence, artificial-intelligence, technology, tech, mlops, llmops</itunes:keywords>
    <itunes:owner>
      <itunes:name>ZenML GmbH</itunes:name>
      <itunes:email>podcast@zenml.io</itunes:email>
    </itunes:owner>
<itunes:category text="Technology"/>
<item>
  <title>ZenML MLOps Competition</title>
  <link>https://podcast.zenml.io/mlops-competition</link>
  <guid isPermaLink="false">20b2e352-4565-487d-ad6e-e0f865c75da5</guid>
  <pubDate>Mon, 26 Sep 2022 14:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
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  <itunes:episodeType>full</itunes:episodeType>
  <itunes:season>2</itunes:season>
  <itunes:author>ZenML GmbH</itunes:author>
  <itunes:subtitle>So excited to be able to announce our :fire: AMAZING :fire: external judges for the ZenML Month of MLOps competition! We have a stellar panel of :sparkles: ML and MLOps heroes :sparkles: to help select the best pipelines from all of your submissions! </itunes:subtitle>
  <itunes:duration>8:13</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>So excited to be able to announce our 🔥 AMAZING 🔥 external judges for the ZenML Month of MLOps competition! We have a stellar panel of ✨ ML and MLOps heroes ✨ to help select the best pipelines from all of your submissions! 
💥 Charles Frye, core instructor at the amazing Full Stack Deep Learning course
💥 Anthony Goldbloom, co-founder and former CEO of Kaggle
💥 Chip Huyen, author of 'Designing Machine Learning Systems' and co-founder of Claypot AI
💥 Goku Mohandas, founder of MadeWithML, another essential course in production ML
We're honoured to have them on board for the ride, and we can't wait to see all the amazing ML use cases and problems our competitors solve along the way!
To learn more about the competition and to sign up, visit https://zenml.io/competition 
</description>
  <itunes:keywords>zenml, mlops, open-source, competition</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>So excited to be able to announce our 🔥 AMAZING 🔥 external judges for the ZenML Month of MLOps competition! We have a stellar panel of ✨ ML and MLOps heroes ✨ to help select the best pipelines from all of your submissions! </p>

<p>💥 Charles Frye, core instructor at the amazing Full Stack Deep Learning course<br>
💥 Anthony Goldbloom, co-founder and former CEO of Kaggle<br>
💥 Chip Huyen, author of &#39;Designing Machine Learning Systems&#39; and co-founder of Claypot AI<br>
💥 Goku Mohandas, founder of MadeWithML, another essential course in production ML</p>

<p>We&#39;re honoured to have them on board for the ride, and we can&#39;t wait to see all the amazing ML use cases and problems our competitors solve along the way!</p>

<p>To learn more about the competition and to sign up, visit <a href="https://zenml.io/competition" rel="nofollow">https://zenml.io/competition</a></p><p>Links:</p><ul><li><a title="Sign Up for the Competition" rel="nofollow" href="https://zenml.io/competition">Sign Up for the Competition</a></li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>So excited to be able to announce our 🔥 AMAZING 🔥 external judges for the ZenML Month of MLOps competition! We have a stellar panel of ✨ ML and MLOps heroes ✨ to help select the best pipelines from all of your submissions! </p>

<p>💥 Charles Frye, core instructor at the amazing Full Stack Deep Learning course<br>
💥 Anthony Goldbloom, co-founder and former CEO of Kaggle<br>
💥 Chip Huyen, author of &#39;Designing Machine Learning Systems&#39; and co-founder of Claypot AI<br>
💥 Goku Mohandas, founder of MadeWithML, another essential course in production ML</p>

<p>We&#39;re honoured to have them on board for the ride, and we can&#39;t wait to see all the amazing ML use cases and problems our competitors solve along the way!</p>

<p>To learn more about the competition and to sign up, visit <a href="https://zenml.io/competition" rel="nofollow">https://zenml.io/competition</a></p><p>Links:</p><ul><li><a title="Sign Up for the Competition" rel="nofollow" href="https://zenml.io/competition">Sign Up for the Competition</a></li></ul>]]>
  </itunes:summary>
</item>
<item>
  <title>ZenML Recap with Adam and Hamza</title>
  <link>https://podcast.zenml.io/zenml-recap-adam-hamza</link>
  <guid isPermaLink="false">8ce789d5-23c4-4251-933d-c4797ea40684</guid>
  <pubDate>Thu, 28 Apr 2022 12:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
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  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>ZenML GmbH</itunes:author>
  <itunes:subtitle>Adam and Hamza return for a short discussion of what we've been busy working on during the previous few months, where we're going with ZenML and why it's so amazing to be building an open-source tool.</itunes:subtitle>
  <itunes:duration>25:31</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>Adam and Hamza return for a short discussion of what we've been busy working on during the previous few months, where we're going with ZenML and why it's so amazing to be building an open-source tool. 
</description>
  <itunes:keywords>zenml, mlops, open-source</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>Adam and Hamza return for a short discussion of what we&#39;ve been busy working on during the previous few months, where we&#39;re going with ZenML and why it&#39;s so amazing to be building an open-source tool.</p>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>Adam and Hamza return for a short discussion of what we&#39;ve been busy working on during the previous few months, where we&#39;re going with ZenML and why it&#39;s so amazing to be building an open-source tool.</p>]]>
  </itunes:summary>
</item>
<item>
  <title>Open-Source MLOps with Matt Squire</title>
  <link>https://podcast.zenml.io/open-source-mlops-matt-squire</link>
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  <pubDate>Thu, 31 Mar 2022 11:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/4d525632-f8ef-47c1-9321-20f5c498b1ac/3d58b3bb-2933-41cd-a32f-0c59343c894a.mp3" length="35090405" type="audio/mpeg"/>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>ZenML GmbH</itunes:author>
  <itunes:subtitle>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.</itunes:subtitle>
  <itunes:duration>47:41</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>This week I spoke with Matt Squire, the CTO and co-founder of Fuzzy Labs (https://www.fuzzylabs.ai), where they help partner organisations think through how best to productionise their machine learning workflows.
Matt and FuzzyLabs are also behind the Awesome Open Source MLOps (https://github.com/fuzzylabs/awesome-open-mlops) GitHub repo where you can find all the options for an open-source MLOps stack of your dreams.
Matt has been an enthusiastic early supporter of the work we do at ZenML so it was really amazing to get to talk to him and  get his take based on the many experiences he's had seeing how ML is done out in the field. Special Guest: Matt Squire.
</description>
  <itunes:keywords>mlops, machine-learning, data-science, ai, artificial-intelligence, infrastructure, open-source</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>This week I spoke with Matt Squire, the CTO and co-founder of <a href="https://www.fuzzylabs.ai" rel="nofollow">Fuzzy Labs</a>, where they help partner organisations think through how best to productionise their machine learning workflows.</p>

<p>Matt and FuzzyLabs are also behind the <a href="https://github.com/fuzzylabs/awesome-open-mlops" rel="nofollow">Awesome Open Source MLOps</a> GitHub repo where you can find all the options for an open-source MLOps stack of your dreams.</p>

<p>Matt has been an enthusiastic early supporter of the work we do at ZenML so it was really amazing to get to talk to him and  get his take based on the many experiences he&#39;s had seeing how ML is done out in the field.</p><p>Special Guest: Matt Squire.</p><p>Links:</p><ul><li><a title="Matt Squire | LinkedIn" rel="nofollow" href="https://www.linkedin.com/in/matt-squire-a19896125/">Matt Squire | LinkedIn</a></li><li><a title="Open Source MLOps - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/">Open Source MLOps - Fuzzy Labs</a></li><li><a title="fuzzylabs/awesome-open-mlops: The Fuzzy Labs guide to the universe of open source MLOps" rel="nofollow" href="https://github.com/fuzzylabs/awesome-open-mlops">fuzzylabs/awesome-open-mlops: The Fuzzy Labs guide to the universe of open source MLOps</a></li><li><a title="Evidently AI - Open-Source Machine Learning Monitoring" rel="nofollow" href="https://evidentlyai.com/">Evidently AI - Open-Source Machine Learning Monitoring</a></li><li><a title="Data Version Control · DVC" rel="nofollow" href="https://dvc.org/">Data Version Control · DVC</a></li><li><a title="Blog - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/blog">Blog - Fuzzy Labs</a></li><li><a title="The Road to Zen: getting started with pipelines - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/blog-post/the-road-to-zen-part-1-getting-started-pipelines">The Road to Zen: getting started with pipelines - Fuzzy Labs</a></li><li><a title="The Road to Zen: running experiments - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/blog-post/the-road-to-zen-running-experiments">The Road to Zen: running experiments - Fuzzy Labs</a></li><li><a title="Guides to MLOps - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/guides">Guides to MLOps - Fuzzy Labs</a></li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>This week I spoke with Matt Squire, the CTO and co-founder of <a href="https://www.fuzzylabs.ai" rel="nofollow">Fuzzy Labs</a>, where they help partner organisations think through how best to productionise their machine learning workflows.</p>

<p>Matt and FuzzyLabs are also behind the <a href="https://github.com/fuzzylabs/awesome-open-mlops" rel="nofollow">Awesome Open Source MLOps</a> GitHub repo where you can find all the options for an open-source MLOps stack of your dreams.</p>

<p>Matt has been an enthusiastic early supporter of the work we do at ZenML so it was really amazing to get to talk to him and  get his take based on the many experiences he&#39;s had seeing how ML is done out in the field.</p><p>Special Guest: Matt Squire.</p><p>Links:</p><ul><li><a title="Matt Squire | LinkedIn" rel="nofollow" href="https://www.linkedin.com/in/matt-squire-a19896125/">Matt Squire | LinkedIn</a></li><li><a title="Open Source MLOps - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/">Open Source MLOps - Fuzzy Labs</a></li><li><a title="fuzzylabs/awesome-open-mlops: The Fuzzy Labs guide to the universe of open source MLOps" rel="nofollow" href="https://github.com/fuzzylabs/awesome-open-mlops">fuzzylabs/awesome-open-mlops: The Fuzzy Labs guide to the universe of open source MLOps</a></li><li><a title="Evidently AI - Open-Source Machine Learning Monitoring" rel="nofollow" href="https://evidentlyai.com/">Evidently AI - Open-Source Machine Learning Monitoring</a></li><li><a title="Data Version Control · DVC" rel="nofollow" href="https://dvc.org/">Data Version Control · DVC</a></li><li><a title="Blog - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/blog">Blog - Fuzzy Labs</a></li><li><a title="The Road to Zen: getting started with pipelines - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/blog-post/the-road-to-zen-part-1-getting-started-pipelines">The Road to Zen: getting started with pipelines - Fuzzy Labs</a></li><li><a title="The Road to Zen: running experiments - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/blog-post/the-road-to-zen-running-experiments">The Road to Zen: running experiments - Fuzzy Labs</a></li><li><a title="Guides to MLOps - Fuzzy Labs" rel="nofollow" href="https://www.fuzzylabs.ai/guides">Guides to MLOps - Fuzzy Labs</a></li></ul>]]>
  </itunes:summary>
</item>
<item>
  <title>Creating Tools that Spark Joy with Ines Montani</title>
  <link>https://podcast.zenml.io/ines-montani</link>
  <guid isPermaLink="false">137ca303-bc89-4424-ad78-37be0158a842</guid>
  <pubDate>Thu, 13 Jan 2022 17:00:00 +0100</pubDate>
  <author>ZenML GmbH</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/4d525632-f8ef-47c1-9321-20f5c498b1ac/137ca303-bc89-4424-ad78-37be0158a842.mp3" length="32272726" type="audio/mpeg"/>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>ZenML GmbH</itunes:author>
  <itunes:subtitle>Our guest this week is Ines Montani, co-founder and CEO of Explosion, a company based out of Berlin that produce tools that you probably know and love like Spacy, a Python Natural Language Processing library and Prodigy, a data annotation tool.</itunes:subtitle>
  <itunes:duration>43:46</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://media24.fireside.fm/file/fireside-images-2024/podcasts/images/4/4d525632-f8ef-47c1-9321-20f5c498b1ac/episodes/1/137ca303-bc89-4424-ad78-37be0158a842/cover.jpg?v=1"/>
  <description>Our guest this week is Ines Montani, co-founder and CEO of Explosion, a company based out of Berlin that produce tools that you probably know and love like Spacy, a Python Natural Language Processing library and Prodigy, a data annotation tool.
I've always found Ines to be personally inspiring in the work that she and her team produce as well as how they present themselves to the world, so it was a real pleasure to get to dive into the weeds as to exactly how that happens. We also discuss how NLP works in production, what reproducibility means for ML projects and much more. Special Guest: Ines Montani.
</description>
  <itunes:keywords>mlops, machine-learning, data-science, nlp, natural-language-processing, open-source</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>Our guest this week is Ines Montani, co-founder and CEO of Explosion, a company based out of Berlin that produce tools that you probably know and love like Spacy, a Python Natural Language Processing library and Prodigy, a data annotation tool.</p>

<p>I&#39;ve always found Ines to be personally inspiring in the work that she and her team produce as well as how they present themselves to the world, so it was a real pleasure to get to dive into the weeds as to exactly how that happens. We also discuss how NLP works in production, what reproducibility means for ML projects and much more.</p><p>Special Guest: Ines Montani.</p><p>Links:</p><ul><li><a title="ines.io" rel="nofollow" href="https://ines.io/">ines.io</a></li><li><a title="Explosion · Makers of spaCy, Prodigy, and other AI and NLP developer tools" rel="nofollow" href="https://explosion.ai/">Explosion · Makers of spaCy, Prodigy, and other AI and NLP developer tools</a></li><li><a title="Software · Explosion" rel="nofollow" href="https://explosion.ai/software#spacy">Software · Explosion</a></li><li><a title="spaCy · Industrial-strength Natural Language Processing in Python" rel="nofollow" href="https://spacy.io/">spaCy · Industrial-strength Natural Language Processing in Python</a></li><li><a title="explosion/spaCy: 💫 Industrial-strength Natural Language Processing (NLP) in Python" rel="nofollow" href="https://github.com/explosion/spaCy">explosion/spaCy: 💫 Industrial-strength Natural Language Processing (NLP) in Python</a></li><li><a title="Prodigy · An annotation tool for AI, Machine Learning &amp; NLP" rel="nofollow" href="https://prodi.gy/">Prodigy · An annotation tool for AI, Machine Learning &amp; NLP</a></li><li><a title="Live Demo · Prodigy · An annotation tool for AI, Machine Learning &amp; NLP" rel="nofollow" href="https://prodi.gy/demo">Live Demo · Prodigy · An annotation tool for AI, Machine Learning &amp; NLP</a></li><li><a title="Thinc · A refreshing functional take on deep learning" rel="nofollow" href="https://thinc.ai/">Thinc · A refreshing functional take on deep learning</a></li><li><a title="explosion/thinc: 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries" rel="nofollow" href="https://github.com/explosion/thinc">explosion/thinc: 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries</a></li><li><a title="ines/spacy-course: 👩‍🏫 Advanced NLP with spaCy: A free online course" rel="nofollow" href="https://github.com/ines/spacy-course">ines/spacy-course: 👩‍🏫 Advanced NLP with spaCy: A free online course</a></li><li><a title="&quot;Let Them Write Code&quot; - Keynote - Ines Montani - YouTube" rel="nofollow" href="https://www.youtube.com/watch?v=Ivb4AAuj5JY">"Let Them Write Code" - Keynote - Ines Montani - YouTube</a></li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>Our guest this week is Ines Montani, co-founder and CEO of Explosion, a company based out of Berlin that produce tools that you probably know and love like Spacy, a Python Natural Language Processing library and Prodigy, a data annotation tool.</p>

<p>I&#39;ve always found Ines to be personally inspiring in the work that she and her team produce as well as how they present themselves to the world, so it was a real pleasure to get to dive into the weeds as to exactly how that happens. We also discuss how NLP works in production, what reproducibility means for ML projects and much more.</p><p>Special Guest: Ines Montani.</p><p>Links:</p><ul><li><a title="ines.io" rel="nofollow" href="https://ines.io/">ines.io</a></li><li><a title="Explosion · Makers of spaCy, Prodigy, and other AI and NLP developer tools" rel="nofollow" href="https://explosion.ai/">Explosion · Makers of spaCy, Prodigy, and other AI and NLP developer tools</a></li><li><a title="Software · Explosion" rel="nofollow" href="https://explosion.ai/software#spacy">Software · Explosion</a></li><li><a title="spaCy · Industrial-strength Natural Language Processing in Python" rel="nofollow" href="https://spacy.io/">spaCy · Industrial-strength Natural Language Processing in Python</a></li><li><a title="explosion/spaCy: 💫 Industrial-strength Natural Language Processing (NLP) in Python" rel="nofollow" href="https://github.com/explosion/spaCy">explosion/spaCy: 💫 Industrial-strength Natural Language Processing (NLP) in Python</a></li><li><a title="Prodigy · An annotation tool for AI, Machine Learning &amp; NLP" rel="nofollow" href="https://prodi.gy/">Prodigy · An annotation tool for AI, Machine Learning &amp; NLP</a></li><li><a title="Live Demo · Prodigy · An annotation tool for AI, Machine Learning &amp; NLP" rel="nofollow" href="https://prodi.gy/demo">Live Demo · Prodigy · An annotation tool for AI, Machine Learning &amp; NLP</a></li><li><a title="Thinc · A refreshing functional take on deep learning" rel="nofollow" href="https://thinc.ai/">Thinc · A refreshing functional take on deep learning</a></li><li><a title="explosion/thinc: 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries" rel="nofollow" href="https://github.com/explosion/thinc">explosion/thinc: 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries</a></li><li><a title="ines/spacy-course: 👩‍🏫 Advanced NLP with spaCy: A free online course" rel="nofollow" href="https://github.com/ines/spacy-course">ines/spacy-course: 👩‍🏫 Advanced NLP with spaCy: A free online course</a></li><li><a title="&quot;Let Them Write Code&quot; - Keynote - Ines Montani - YouTube" rel="nofollow" href="https://www.youtube.com/watch?v=Ivb4AAuj5JY">"Let Them Write Code" - Keynote - Ines Montani - YouTube</a></li></ul>]]>
  </itunes:summary>
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