From Idea to Production ML, From Idea to Production ML, From Idea to Production ML

Name: From%20Idea%20to%20Production%20ML,%20From%20Idea%20to%20Production%20ML,%20From%20Idea%20to%20Production%20ML
Uploaded: 2021-04-28

Posted Apr 28, 2021 | Views 748

# Googler

# Panel

# Interview

# Monitoring

speakers

Lex Beattie

ML Engagement Lead @ Spotify

Lex Beattie is the Machine Learning Engagement Lead at Spotify. In the last year, she has helped over 40 different teams across Spotify understand ML best practices, productionize ML workflows and implement impactful ML in their products. Lex is also a Ph.D. candidate at the University of Oklahoma, focusing on feature importance and interpretability in deep neural networks. Beyond her passion for all things ML, she enjoys exploring the great outdoors in Montana with her German Wirehaired Pointer, Bridger.

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Michael Munn

ML Solutions Engineer @ Google

Michael is an ML Solutions Engineer with Google Cloud and Google's Advanced Solutions Lab. In his role, he works with customers to build and deploy end-to-end ML solutions with Google Cloud. Within the Advanced Solutions Lab, he teaches these skills to customers.

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Mike Moran

Principal Engineer @ Skyscanner

Mike has worked across many dimensions; in large/tiny companies, back-end/front-end, with many languages, and as a sys-admin /engineer/manager.

Mike has a healthy skepticism for most things and likes solving problems through applying System thinking.

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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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SUMMARY

We started out talking about some of the main bottlenecks they have encountered over the years of trying to push data products into production environments. Then things started to heat up as we dove into the topic of monitoring ML and inevitably the word explainability started being thrown around. Turns out Lex is currently doing a Ph.D. on the subject so there was much to talk about. We had to ask if explainability is now table-stakes when it comes to monitoring solutions on the market? The short answer from the team. Yes! Please excuse the bit of sound trouble we had with google mike at the beginning., We started out talking about some of the main bottlenecks they have encountered over the years of trying to push data products into production environments. Then things started to heat up as we dove into the topic of monitoring ML and inevitably the word explainability started being thrown around. Turns out Lex is currently doing a Ph.D. on the subject so there was much to talk about. We had to ask if explainability is now table-stakes when it comes to monitoring solutions on the market? The short answer from the team. Yes! Please excuse the bit of sound trouble we had with google mike at the beginning., We started out talking about some of the main bottlenecks they have encountered over the years of trying to push data products into production environments. Then things started to heat up as we dove into the topic of monitoring ML and inevitably the word explainability started being thrown around. Turns out Lex is currently doing a Ph.D. on the subject so there was much to talk about. We had to ask if explainability is now table-stakes when it comes to monitoring solutions on the market? The short answer from the team. Yes! Please excuse the bit of sound trouble we had with google mike at the beginning.

+ Read More