Data Brew by Databricks
A podcast by Databricks - Thursdays
Categories:
31 Episodes
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Kumo AI & Relational Deep Learning | Data Brew | Episode 34
Published: 14/10/2024 -
LLMs: Internals, Hallucinations, and Applications | Data Brew | Episode 33
Published: 21/07/2023 -
Demonstrate–Search–Predict Framework | Data Brew | Episode 32
Published: 29/06/2023 -
Generative AI Risks | Data Brew | Episode 31
Published: 8/06/2023 -
John Snow Labs & SparkNLP | Data Brew | Episode 30
Published: 1/06/2023 -
Data Brew Season 4 Episode 6: Professional Athletes
Published: 9/06/2022 -
Data Brew Season 4 Episode 5: Public Health: Education, Access, and Policy
Published: 5/05/2022 -
Data Brew Season 4 Episode 4: 1283 Days of Running (and Counting)
Published: 14/04/2022 -
Data Brew Season 4 Episode 3: Last Man Standing
Published: 31/03/2022 -
Data Brew Season 4 Episode 2: NBA Analytics
Published: 10/03/2022 -
Data Brew Season 4 Episode 1: Reducing Injury & Increasing Retention of Industrial Athletes
Published: 24/02/2022 -
Data Brew Season 3 Episode 6: Open Source
Published: 28/10/2021 -
Data Brew Season 3 Episode 5: Sustainability & Sake
Published: 14/10/2021 -
Data Brew Season 3 Episode 4: Executive Education
Published: 7/10/2021 -
Data Brew Season 3 Episode 3: 3 T’s to Securing AI Systems: Tests, tests, and more tests
Published: 30/09/2021 -
Data Brew Season 3 Episode 1: Disrupt: Challenge your Business Assumptions
Published: 16/09/2021 -
Data Brew Season 2 Episode 9: Data Driven Software
Published: 21/07/2021 -
Data Brew Season 2 Episode 8: Feature Engineering
Published: 9/07/2021 -
Data Brew Season 2 Episode 7: Interpretable Machine Learning
Published: 1/07/2021 -
Data Brew Season 2 Episode 6: AutoML
Published: 17/06/2021
Welcome to Data Brew by Databricks with Denny and Brooke! In this series, we explore various topics in the data and AI community and interview subject matter experts in data engineering/data science. So join us with your morning brew in hand and get ready to dive deep into data + AI! For this first season, we will be focusing on lakehouses – combining the key features of data warehouses, such as ACID transactions, with the scalability of data lakes, directly against low-cost object stores.