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

AWS Machine Learning

For example, the true yardage distribution for kickoff and punts are similar but shifted, as shown in the following figure. For evaluation, we kept the metric used in the Kaggle competition, the continuous ranked probability score (CRPS) , which can be seen as an alternative to the log-likelihood that is more robust to outliers.

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Customer Experience Automation – Benefits and Best Practices

NobelBiz

In this article, we delve into the intricacies of CXA, explore its benefits, showcase examples, and outline best practices for implementation. Interactive Voice Response (IVR) At the core of intelligent contact center automation lies a well-calibrated IVR system. Table of Contents What Is Customer Experience Automation (CXA)?

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Face-off Probability, part of NHL Edge IQ: Predicting face-off winners in real time during televised games

AWS Machine Learning

The decision tree provided the cut-offs for each metric, which we included as rules-based logic in the streaming application. At the end, we found that the LightGBM model worked best with well-calibrated accuracy metrics. For examples of using Amazon Kinesis for streaming, refer to Learning Amazon Kinesis Development.

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Auto-labeling module for deep learning-based Advanced Driver Assistance Systems on AWS

AWS Machine Learning

For example, the following figure shows a 3D bounding box around a car in the Point Cloud view for LiDAR data, aligned orthogonal LiDAR views on the side, and seven different camera streams with projected labels of the bounding box. Ground Truth’s automated data labeling functionality is an example of active learning.