Building Real-Time ML Features with Feast, Spark, Redis, and Kafka
Автор: Toronto Machine Learning Society (TMLS)
Загружено: 2023-08-17
Просмотров: 1758
Speakers:
Danny Chiao, Engineering Lead, Tecton
Danny Chiao is an engineering lead at Tecton/Feast working on building a next-generation feature store. Previously, Danny was a technical lead at Google working on end-to-end machine learning problems within Google Workspace, helping build privacy-aware ML platforms / data pipelines and working with research and product teams to deliver large-scale ML-powered enterprise functionality. Danny holds a Bachelor’s degree in Computer Science from MIT.
Achal Shah, Software Engineer, Tecton
Achal Shah works at Tecton and is a tech lead for Feast, the open-source feature store. Before Tecton, Achal worked at Uber on their Machine Learning platform, Michelangelo, along with Tecton's co-founders. Achal has always had a passion for infrastructure design and the open-source community. In his free time, Achal loves to play hide and seek with his 1-year old daughter or read science fiction if she's asleep.
Abstract:
This workshop will focus on the core concepts underlying Feast, the open-source feature store. We’ll explain how Feast integrates with underlying data infrastructure including Spark, Redis, and Kafka, to provide an interface between models and data.
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