Machine Learning Logistics: Model Management in the Real World - TechRepublic

Machine Learning Logistics: Model Management in the Real World

Last Updated: February 12, 2022 Format: PDF

Model Management in the Real World

How do you get a machine learning system to deliver value from big data?

Turns out that 90% of the effort required for success in machine learning is not the algorithm or the model or the learning – it’s the logistics. Ted Dunning and Ellen Friedman identify what matters in machine learning logistics, what challenges arise, especially in a production setting, and they introduce an innovative solution: the rendezvous architecture.

This new design for model management is based on a streaming approach in a microservices style. Rendezvous addresses the need to preserve and share raw data, to do effective model-to-model comparisons and to have new models on standby, ready for a hot hand-off when a production model needs to be replaced.

In this book you’ll learn:

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