Building Real Time ML Pipelines with a Feature Store
MLOps World: Machine Learning in Production via YouTube
Overview
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Explore the intricacies of constructing real-time machine learning pipelines using a feature store in this 31-minute conference talk from MLOps World: Machine Learning in Production. Learn from Gilad Shaham, Director of Product Management at Iguazio, as he shares insights drawn from his extensive 15-year experience in product management and R&D background. Discover how to effectively combine analytical skills and technical innovation with Data Science market experience to define and realize product visions. Gain valuable knowledge about Enterprise MLOps Platform products and MLRun, Iguazio's open-source MLOps orchestration framework. Delve into the challenges of increasing compute demand in Machine Learning and understand why simply investing in more GPUs isn't the optimal solution. Uncover strategies for smarter processing and efficient utilization of computational resources in ML pipelines.
Syllabus
Building Real Time ML Pipelines with a Feature Store
Taught by
MLOps World: Machine Learning in Production