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    <title>Pipeline Conversations - Episodes Tagged with “Serverless”</title>
    <link>https://podcast.zenml.io/tags/serverless</link>
    <pubDate>Thu, 28 Jul 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>Satellite Vision with Robin Cole</title>
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  <pubDate>Thu, 28 Jul 2022 09:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
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  <itunes:subtitle>This week I spoke with Robin Cole, a senior data scientist at Satellite Vu, a company that's about to launch a thermal imaging satellite into space in order to provide new ways of seeing the earth from above.</itunes:subtitle>
  <itunes:duration>47:56</itunes:duration>
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  <description>This week I spoke with Robin Cole, a senior data scientist at Satellite Vu (https://www.satellitevu.com), a company that's about to launch a thermal imaging satellite into space in order to provide new ways of seeing the earth from above.
Robin generously took the time to discuss his day to day work involving satellite data, the stack they work with at Satellite Vu as well as some of the difficulties that come up in the domain. We also discuss the extremely popular satellite-image-deep-learning GitHub repo (https://github.com/robmarkcole/satellite-image-deep-learning) that presents resources for those working with or seeking to learn about this kind of data. Special Guest: Robin Cole.
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    <![CDATA[<p>This week I spoke with Robin Cole, a senior data scientist at <a href="https://www.satellitevu.com" rel="nofollow">Satellite Vu</a>, a company that&#39;s about to launch a thermal imaging satellite into space in order to provide new ways of seeing the earth from above.</p>

<p>Robin generously took the time to discuss his day to day work involving satellite data, the stack they work with at Satellite Vu as well as some of the difficulties that come up in the domain. We also discuss the extremely popular <a href="https://github.com/robmarkcole/satellite-image-deep-learning" rel="nofollow">satellite-image-deep-learning GitHub repo</a> that presents resources for those working with or seeking to learn about this kind of data.</p><p>Special Guest: Robin Cole.</p><p>Links:</p><ul><li><a title="About Us — Satellite Vu" rel="nofollow" href="https://www.satellitevu.com/about-us">About Us — Satellite Vu</a></li><li><a title="Satellite Vu (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/company/satellitevu/">Satellite Vu (LinkedIn)</a></li><li><a title="Satellite Vu prepares to launch its thermal imaging satellite constellation with $21M A round | TechCrunch" rel="nofollow" href="https://techcrunch.com/2022/03/01/satellite-vu-prepares-to-launch-its-thermal-imaging-satellite-constellation-with-21m-a-round/">Satellite Vu prepares to launch its thermal imaging satellite constellation with $21M A round | TechCrunch</a></li><li><a title="robmarkcole/satellite-image-deep-learning: Resources for deep learning with satellite &amp; aerial imagery" rel="nofollow" href="https://github.com/robmarkcole/satellite-image-deep-learning">robmarkcole/satellite-image-deep-learning: Resources for deep learning with satellite &amp; aerial imagery</a></li><li><a title="Robin Cole (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/in/robmarkcole/">Robin Cole (LinkedIn)</a></li><li><a title="GeoTIFF - Wikipedia" rel="nofollow" href="https://en.wikipedia.org/wiki/GeoTIFF">GeoTIFF - Wikipedia</a></li></ul>]]>
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    <![CDATA[<p>This week I spoke with Robin Cole, a senior data scientist at <a href="https://www.satellitevu.com" rel="nofollow">Satellite Vu</a>, a company that&#39;s about to launch a thermal imaging satellite into space in order to provide new ways of seeing the earth from above.</p>

<p>Robin generously took the time to discuss his day to day work involving satellite data, the stack they work with at Satellite Vu as well as some of the difficulties that come up in the domain. We also discuss the extremely popular <a href="https://github.com/robmarkcole/satellite-image-deep-learning" rel="nofollow">satellite-image-deep-learning GitHub repo</a> that presents resources for those working with or seeking to learn about this kind of data.</p><p>Special Guest: Robin Cole.</p><p>Links:</p><ul><li><a title="About Us — Satellite Vu" rel="nofollow" href="https://www.satellitevu.com/about-us">About Us — Satellite Vu</a></li><li><a title="Satellite Vu (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/company/satellitevu/">Satellite Vu (LinkedIn)</a></li><li><a title="Satellite Vu prepares to launch its thermal imaging satellite constellation with $21M A round | TechCrunch" rel="nofollow" href="https://techcrunch.com/2022/03/01/satellite-vu-prepares-to-launch-its-thermal-imaging-satellite-constellation-with-21m-a-round/">Satellite Vu prepares to launch its thermal imaging satellite constellation with $21M A round | TechCrunch</a></li><li><a title="robmarkcole/satellite-image-deep-learning: Resources for deep learning with satellite &amp; aerial imagery" rel="nofollow" href="https://github.com/robmarkcole/satellite-image-deep-learning">robmarkcole/satellite-image-deep-learning: Resources for deep learning with satellite &amp; aerial imagery</a></li><li><a title="Robin Cole (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/in/robmarkcole/">Robin Cole (LinkedIn)</a></li><li><a title="GeoTIFF - Wikipedia" rel="nofollow" href="https://en.wikipedia.org/wiki/GeoTIFF">GeoTIFF - Wikipedia</a></li></ul>]]>
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