Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Machine Learning Logistics

Model Management in the Real World

To succeed with machine learning or deep learning, you need an effective management system for overall data flow and the evaluation and deployment of multiple models as they move from prototype to production. Without that, your project will most likely fail. This ebook examines what you need for effective data and model management in real-world settings, including globally distributed cloud or on-premises systems.

This ebook is ideal for data scientists, architects, developers, ops teams, and project managers—whether your team is planning to build a machine learning system, or currently has one underway.

You'll learn:

  • Issues in ML logistics to consider when designing and implementing your system
  • How the rendezvous architecture leverages streaming data, provides hot hand-off of new models, and collects diagnostic data
  • Practical tips for comparing live models, including the role of decoys, canaries and the t-digest
  • Best practices for maintaining performance after deployment

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Get unparalleled depth and breadth in machine and deep learning at Strata

Make plans to attend Strata Data Conference, taking place March 5-8 in San Jose—with an expanded Data Science and Machine Learning program featuring sessions in deep learning, Tensorflow, PyTorch, NLP, explainable AI, ML applications in industry, and much more.