On Juggling, Dr. Seuss and Feature Stores for Real-time AI/ML
Posted May 30, 2022 | Views 674
# Juggling
# Dr. Seuss
# Feature Stores
# Real-time AI/ML
# Redis.io
Share
SPEAKERS
Nava Levy
Developer Advocate for Data Science and MLOps @ Redis
Nava is a Developer Advocate for Data Science and MLOps at Redis. She started her career in tech with an R&D Unit in the IDF and later had the good fortune to work with and champion Cloud, Big Data, and DL/ML/AI technologies just as the wave of each of these was starting.
Nava is also a mentor at the MassChallenge accelerator and the founder of LerGO—a cloud-based EdTech venture. In her free time, she enjoys cycling, 4-ball juggling, and reading fantasy and sci-fi books.
+ Read More
Nava is a Developer Advocate for Data Science and MLOps at Redis. She started her career in tech with an R&D Unit in the IDF and later had the good fortune to work with and champion Cloud, Big Data, and DL/ML/AI technologies just as the wave of each of these was starting.
Nava is also a mentor at the MassChallenge accelerator and the founder of LerGO—a cloud-based EdTech venture. In her free time, she enjoys cycling, 4-ball juggling, and reading fantasy and sci-fi books.
+ Read More
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.
+ Read More
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.
+ Read More
SUMMARY
Real-time ML-based applications are on the rise but deploying them at scale for large datasets with low latency and high throughput is challenging. This talk discusses the important role of feature stores for machine learning in deploying these applications.
By exploring a number of use cases in production, we see how the choice of online data store and the feature store data architecture play important roles in determining its performance and cost. Throughout the presentation, Nava illustrates key points by connecting them to juggling and Dr. Seuss! Stay tuned :)