
This episode of our MLOps Weekly Podcast features Simba Khadder, Featureform’s CEO, where he unravels the true meaning of “real-time” machine learning. The discussion breaks down real-time ML into three core aspects: latency, online serving, and real-time features. Simba also covers:How latency impacts the speed of ML systemsThe distinctions between online and offline modelsReal-time features and the importance of a balance between data freshness and latencyThis podcast will give listeners a better understanding of these concepts and apply them to their own ML projects.
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MLOps Week 32: MLOps and Feature Stores in 2025 with Ben Epstein

MLOps Week 31: Bridging Software Engineering and MLOps with Paul lusztin of Decoding ML

MLOps Week 30 - From Recession to Al Boom: Venture Capital Perspectives with Gautam Krishnamurthi

MLOps Week 29: Building the Future of ML Platforms with Ketan Umare
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