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Pipeline Conversations
ZenML GmbH
34 episodes
8 months ago
Pipeline Conversations is a fortnightly podcast bringing you interviews and discussion with industry leaders, top technology professionals and others. We discuss the latest developments in machine learning, deep learning, artificial intelligence, with a particular focus on MLOps, or how trained models are used in production.
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Technology
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All content for Pipeline Conversations is the property of ZenML GmbH and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Pipeline Conversations is a fortnightly podcast bringing you interviews and discussion with industry leaders, top technology professionals and others. We discuss the latest developments in machine learning, deep learning, artificial intelligence, with a particular focus on MLOps, or how trained models are used in production.
Show more...
Technology
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ML at the British Library with Daniel van Strien
Pipeline Conversations
57 minutes 28 seconds
2 years ago
ML at the British Library with Daniel van Strien

This week I spoke with Daniel van Strien, a digital curator working at the British Library. Daniel has worked on a number of projects at the intersection of archives, libraries and machine learning and I was really happy to have the chance to get to unpack some of the ways he's finding to apply these techniques and tools.

In particular, I found it interesting how important the annotation process is as part of many overall workflows, as well as how simple out-of-the-box techniques like image classification using a fine-tuned model could satisfy many low-hanging fruit-type use cases.

Special Guest: Daniel van Strien.

Pipeline Conversations
Pipeline Conversations is a fortnightly podcast bringing you interviews and discussion with industry leaders, top technology professionals and others. We discuss the latest developments in machine learning, deep learning, artificial intelligence, with a particular focus on MLOps, or how trained models are used in production.