YouTube: http://www.youtube.com/watch?v=GiSU696iCcg
According to the description of the lecture: "Taking data science into action requires deploying statistical models into production environments, usually with real-time processing requirements. Every company that relies on predictive models to drive their applications and operations has a different process for model deployment, but by working with many such companies I’ve seen a common pattern emerge. The real-time model deployment process can be broken down into these five stages:
- Data distillation
- Model development
- Model validation and deployment
- Model refresh
- Real-time model scoring."
It's Worth Watching!
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