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Model Performance Monitoring and Why You Need it Yesterday

Posted Jun 01, 2021 | Views 519
# Machine Learning
# ML Monitoring
# Fiddler AI
# Fiddler.ai
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SPEAKERS
Amit Paka
Amit Paka
Amit Paka
CPO & Co-founder @ Fiddler AI

Amit is the co-founder and CPO of Fiddler, a Machine Learning Monitoring company that empowers companies to efficiently monitor and troubleshoot ML models with Explainable AI. Prior to founding Fiddler, Paka led the shopping apps product team at Samsung. Paka founded Parable, the Creative Photo Network, now part of the Samsung family. He also led PayPal's consumer in-store mobile payments launching innovations like hardware beacon payments, and has developed successful startup products particularly in online advertising - paid search, contextual, ad exchange and display advertising. Paka has passions for actualizing new concepts, building great teams and pushing the envelope, and aims to leverage these skills to help define how AI can be fair, ethical and responsible.

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Amit is the co-founder and CPO of Fiddler, a Machine Learning Monitoring company that empowers companies to efficiently monitor and troubleshoot ML models with Explainable AI. Prior to founding Fiddler, Paka led the shopping apps product team at Samsung. Paka founded Parable, the Creative Photo Network, now part of the Samsung family. He also led PayPal's consumer in-store mobile payments launching innovations like hardware beacon payments, and has developed successful startup products particularly in online advertising - paid search, contextual, ad exchange and display advertising. Paka has passions for actualizing new concepts, building great teams and pushing the envelope, and aims to leverage these skills to help define how AI can be fair, ethical and responsible.

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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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Vishnu Rachakonda
Vishnu Rachakonda
Vishnu Rachakonda
Data Scientist @ Firsthand

Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.

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Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.

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SUMMARY

Machine Learning accelerates business growth but is prone to performance degradation due to its high reliance on data. Moreover, MLOps is often fragmented in many organizations, causing frictions to debug models in production. With new rules from EU that focus on trust and transparency, it’s becoming more important to keep track of model performance. But how? We propose a new framework, a centralized ML Model Performance Management powered by Explainable AI. Learn more about how you can stay compliant while maximizing your model performance at all times with explainability and continuous monitoring.

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