So you built a model; now what? (sponsored by Dataiku)
Jed Dougherty takes a deep dive into an often overlooked aspect of the data science lifecycle: model deployment. Once they’ve constructed a data science model that does a good job accurately predicting their test set, many data scientists think the job is over. But really, it’s just begun.
Jed explores tracking model quality, updating models in production, benchmarking model API response times, A/B testing, and deciding on cluster deployment strategies.
This session is sponsored by Dataiku.
What you'll learn
- Discover what you still have left to do once you've built your model
Jed Dougherty is a data scientist at Dataiku, where he leads the data scientist team in North America. He specializes in helping large companies in fields including finance, manufacturing, and medicine spin up and organize data science teams and has helped clients build successful projects in data security, real-time recommendation, predictive maintenance, and other “hot topics.” Previously, he worked at a camel ride, so he’s spent quite a bit of time appreciating the normal versus bimodal distribution of dromedaries and Bactrians. He holds a master’s degree from the QMSS program at Columbia University.
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