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How to Build a Reproducible ML Pipeline

15:30 - 16:15 (GMT+03:00)
12 November 2020
Keynote
Add to calendar 11/12/2020 15:30 11/12/2020 16:15 Europe/Bucharest GoTech World 2020 - The New Reality - How to Build a Reproducible ML Pipeline Only with PRO Pass
https://myconnector.ro/virtual/gotech-world-2020--the-new-reality/423
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Solving a data science problem usually requires multiple steps. These steps can include extracting and transforming data, training a model, and deploying the model into production.

In this session, we'll discuss how to specify those steps with Python into an ML pipeline. We'll show how to create a Kubeflow Pipeline, a component of the Kubeflow open-source project. The audience will learn about how to integrate TensorFlow Extended components into the pipeline, and how to deploy the pipeline to the hosted Cloud AI Pipelines environment on Google Cloud. The key takeaway is how to improve reuse and reproducibility of the machine learning process.
 

Karl Weinmeister
Karl Weinmeister
Cloud AI Developer Advocacy Manager
Google
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Karl Weinmeister is a Cloud AI Advocacy Manager at Google, where he leads a team of data science experts who develop content and engage with communities worldwide. Karl has worked extensively in machine learning and cloud technologies. He was a contributor to one of the first AI-based crossword puzzle solvers that is still referenced today.



10:00 - 10:15 (GMT)
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10:15 - 10:45 (GMT)
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10:45 - 11:15 (GMT)
12 November 2020
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11:15 - 11:45 (GMT)
12 November 2020
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11:45 - 12:30 (GMT)
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12:30 - 13:15 (GMT)
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Networking Break
13:15 - 14:00 (GMT)
12 November 2020
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14:00 - 14:45 (GMT)
12 November 2020
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14:45 - 15:00 (GMT)
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Networking Break
15:00 - 15:30 (GMT)
12 November 2020
Keynote
Watching
How to Build a Reproducible ML Pipeline
15:30 - 16:15 (GMT)
12 November 2020
Keynote
16:15 - 16:30 (GMT)
12 November 2020
Networking Break
16:30 - 17:15 (GMT)
12 November 2020
Keynote