War Stories Productionising ML

Name: War%20Stories%20Productionising%20ML
Uploaded: 2021-04-20

Posted Apr 20, 2021 | Views 389

# Marks and Spencer

# Machine Learning

# marksandspencer.com

speakers

Nick Masca

Head of Data Science @ Marks and Spencer

Nick currently serves as a Head of Data Science at Marks and Spencer, a large retailer based in the UK. With a background originally in statistics, he transitioned into data science in 2014 and has picked up many battle scars and learnings since.

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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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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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SUMMARY

A conversation with MLOps war stories. Better said, a war story conversation. The kind that informs modern MLOps best practices. Nick shared how to make MLOps organizational changes at large companies. I loved one tidbit he mentioned--"it's an evolution, not a revolution". That's a frank observation about the speed of practical change. As we all know it doesn't happen overnight. Another great learning Nick shared focused on the value of delivering incremental results regularly. Oftentimes, ML projects suffer because of a focus on delivering too much too soon. This can then lead to a trough of disappointment with the way things actually pan out. Nick shared his experience on how to avoid such pitfalls with us so you don't have to learn the hard way.

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