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

Flipboard

The player tracking data contains the player’s position, direction, acceleration, and more (in x,y coordinates). There are around 3,000 and 4,000 plays from four NFL seasons (2018–2021) for punt and kickoff plays, respectively. The data distribution for punt and kickoff are different.

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Present and future of data cubes: an European EO perspective

Mlearning.ai

It can be gradually “enriched” so the typical hierarchy of data is thus: Raw dataCleaned data ↓ Analysis-ready data ↓ Decision-ready data ↓ Decisions. For example, vector maps of roads of an area coming from different sources is the raw data. 2018, July). Remote Sensing, 12(24), 4033.

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Identifying defense coverage schemes in NFL’s Next Gen Stats

AWS Machine Learning Blog

Feature engineering Game tracking data is captured at 10 frames per second, including the player location, speed, acceleration, and orientation. and Big Data Bowl Kaggle Zoo solution ( Gordeev et al. ). He completed his master’s degree in Data Science at Columbia University in the City of New York in December 2019.

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Capital One’s data-centric solutions to banking business challenges

Snorkel AI

Compute, big data, large commoditized models—all important stages. But now we’re entering a period where data investments have massive returns from all performance as well as business impact. To borrow another example from Andrew Ng, improving the quality of data can have a tremendous impact on model performance.

article thumbnail

Capital One’s data-centric solutions to banking business challenges

Snorkel AI

Compute, big data, large commoditized models—all important stages. But now we’re entering a period where data investments have massive returns from all performance as well as business impact. To borrow another example from Andrew Ng, improving the quality of data can have a tremendous impact on model performance.