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KServe Live Coding Session

Posted Oct 27, 2021 | Views 406
# Prosus.com
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SPEAKERS
Theofilos Papapanagiotou
Theofilos Papapanagiotou
Theofilos Papapanagiotou
Data Science Architect @ Prosus

Theo is a recovering Unix Engineer with 20 years of work experience in Telcos, on internet services, video delivery, and cybersecurity. He is also a university student for life; BSc in CS 1999, MSc in Data Coms 2008, and MSc in AI 2017.

Nowadays he calls himself an ML Engineer, as he expresses through this role his passion for System Engineering and Machine Learning. His analytical thinking is driven by curiosity and a hacker’s spirit. He has skills that span a variety of different areas: Statistics, Programming, Databases, Distributed Systems, and Visualization.

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Theo is a recovering Unix Engineer with 20 years of work experience in Telcos, on internet services, video delivery, and cybersecurity. He is also a university student for life; BSc in CS 1999, MSc in Data Coms 2008, and MSc in AI 2017.

Nowadays he calls himself an ML Engineer, as he expresses through this role his passion for System Engineering and Machine Learning. His analytical thinking is driven by curiosity and a hacker’s spirit. He has skills that span a variety of different areas: Statistics, Programming, Databases, Distributed Systems, and Visualization.

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Demetrios Brinkmann
Demetrios Brinkmann
Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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SUMMARY

We start with the serialization of TensorFlow/PyTorch/SKLearn models into files and the deployment of an inference service on a Kubernetes cluster. Great MLOps means great model monitoring, so then we look at inference service metrics, model server metrics, payload logs, class distributions.  For AI ethics on production, we use the explainers pattern with many different explainers, fairness detectors, and adversarial attacks. For integrations, we use the transformer pattern to process as well as to enrich the inference request with online features from a feature store.

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