Remove Accountability Remove Big data Remove Calibration
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Predict football punt and kickoff return yards with fat-tailed distribution using GluonTS

AWS Machine Learning

The player data was used to derive features for model development: X – Player position along the long axis of the field Y – Player position along the short axis of the field S – Speed in yards/second; replaced by Dis*10 to make it more accurate (Dis is the distance in the past 0.1 k10 Baseline 0 4.074 9.62 between the two distributions.

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What to do with a ‘Watermelon Customer’?

CustomerSuccessBox

Now, the concern here is that as a CSM, you could easily overlook a ‘green’ customer account thinking it to be a healthy one! They’re a BIG churn risk. Just imagine the enormity of untracked data. This data can uncover the underlying intent of the customer. This is why the current customer success tools are failing.