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How Is Enterprise Problem Solving Different From Chess,Go,ImageNet, Most Kaggle Challenges And Moonshots

March 12 @ 8:00 am to 5:00 pm

What changes when we try to address enterprise problems? How does problem formulation change what questions can be answered? What happens when our model does not capture the underlying data generating process ? Why does capturing correlations vs establishing causative relationships matter? Does our data even have information on questions we want answered? Does distribution of our production data look like the training data in the enterprise? [No: This assumption is almost always violated] What does it take to answer “what-if this did not happen” questions? We will examine three example problems solved in production to explore what it takes to successfully address problems in the enterprise with a progressive move towards dynamic causal models.

Recordings of the past webinars are available on YouTube

VIKAS AGRAWALSenior Principal Data Scientist,Oracle


March 12
8:00 am - 5:00 pm