Remove Big data Remove Calibration Remove Metrics
article thumbnail

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.

article thumbnail

Model management for LoRA fine-tuned models using Llama2 and Amazon SageMaker

AWS Machine Learning

In the era of big data and AI, companies are continually seeking ways to use these technologies to gain a competitive edge. At the core of these cutting-edge solutions lies a foundation model (FM), a highly advanced machine learning model that is pre-trained on vast amounts of data.

article thumbnail

What to do with a ‘Watermelon Customer’?

CustomerSuccessBox

To identify a watermelon customer, the metric that would help you the most is instead the Customer Intent Score. The Customer Intent Score is a metric that measures a visitor’s willingness to accomplish a conversion goal, for example- a request for further information. This data can uncover the underlying intent of the customer.