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Predict football punt and kickoff return yards with fat-tailed distribution using GluonTS

AWS Machine Learning

The data distribution for punt and kickoff are different. Data preprocessing and feature engineering First, the tracking data was filtered for just the data related to punts and kickoff returns. As a baseline, we used the model that won our NFL Big Data Bowl competition on Kaggle.

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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. Only data and NO insights. Based on rule engines.