Data Brew by Databricks

Latest Episodes:

Data Brew Season 2 Episode 8: Feature Engineering Jul 08, 2021

Show notes

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Is there ever a “one-size fits all” approach for feature engineering? Find out this and more with Amanda Casari and Alice Zheng, co-authors of the Feature Engineering for Machine Learning book.
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Data Brew Season 2 Episode 7: Interpretable Machine Learning Jul 01, 2021

Show notes

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
What does it mean for a model to be “interpretable”? Ameet Talwalkar shares his thoughts on IML (Interpretable Machine Learning), how it relates to data privacy and fairness, and his research in this field.
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Data Brew Season 2 Episode 6: AutoML Jun 17, 2021

Show notes

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Erin LeDell shares valuable insight on AutoML, what problems are best solved by it, its current limitations, and her thoughts on the future of AutoML. We also discuss founding and growing the Women in Machine Learning and Data Science (WiMLDS) non-profit.
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Data Brew Season 2 Episode 5: ML Applications Jun 10, 2021

Show notes

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Good machine learning starts with high quality data. Irina Malkova shares her experience managing and ensuring high-fidelity data, developing custom metrics to satisfy business needs, and discusses how to improve internal decision making processes.
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Data Brew Season 2 Episode 4: Hyperparameter and Neural Architecture Search May 13, 2021

Show notes

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Liam Li is a leading researcher in the fields of hyperparameter optimization and neural architecture search, and is the author of the seminal Hyperband paper. In this session, Liam discusses the evolution of hyperparameter optimization techniques and illustrates how every data scientist can benefit from neural architecture search.
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Data Brew Season 2 Episode 3: Infrastructure for ML May 05, 2021

Show notes

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Adam Oliner discusses how to design your infrastructure to support ML, from integration tests to glue code, the importance of iteration, and centralized vs decentralized data science teams. He provides valuable advice for companies investing in ML and crucial lessons he’s learned from founding two companies.
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Data Brew Season 2 Episode 2: Data Ethics Apr 28, 2021

Show notes

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Have you ever wondered how your purchasing behavior may reveal protected attributes? Or how data scientists and business play a role in combating bias? We discuss with Diana Pfeil recommendations to reduce bias and improve fairness, from SHAP to adversarial debiasing.
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Data Brew Season 2 Episode 1: ML in Production Apr 22, 2021

Show notes

For our second season, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
In the season opener, Matei Zaharia discusses how he entered the field of ML, best practices for productionizing ML pipelines, leveraging MLflow & the Lakehouse architecture for reproducible ML, and his current research in this field.
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Data Brew Season 1 Episode 6: Journey of Big Data Feb 18, 2021

Show notes

Jules Damji and Tathagata Das guide us through their journey in big data and the evolution of data architecture in the past 30 years. They discuss some of the biggest changes in industry they’ve seen, as well as trends to look forward to in the coming years. This is a fun episode connecting all four authors of the Learning Spark, 2nd Edition book.
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Data Brew Season 1 Episode 5: Combining Machine Learning and MLflow with your Lakehouse Jan 06, 2021

Show notes

Ellissa Verseput, ML Engineer at Quby, joins Denny and Brooke to discuss how Quby leverages ML to extract additional value from their data lake and how they manage this process.
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