Flipboard

FEBRUARY 2, 2023

Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season. To avoid leakage during cross-validation, we grouped all plays from the same game into the same fold. Marc van Oudheusden is a Senior Data Scientist with the Amazon ML Solutions Lab team at Amazon Web Services.

Cross Validation 123

Cross Validation ML ML Machine Learning 123

AWS Machine Learning Blog

OCTOBER 3, 2024

Steamlining model management and deployment with SageMaker Amazon SageMaker is a managed machine learning platform that provides data scientists and data engineers familiar concepts and tools to build, train, deploy, govern , and manage the infrastructure needed to have highly available and scalable model inference endpoints.

Data Science 86

Data Science AWS Machine Learning Machine Learning 86

AWS Machine Learning Blog

SEPTEMBER 29, 2023

Amazon SageMaker geospatial capabilities combined with Planet ’s satellite data can be used for crop segmentation, and there are numerous applications and potential benefits of this analysis to the fields of agriculture and sustainability. Xiong Zhou is a Senior Applied Scientist at AWS. Shital Dhakal is a Sr.

Machine Learning 129

Machine Learning Machine Learning ML ML 129

AWS Machine Learning Blog

FEBRUARY 10, 2023

Quantitative evaluation We utilize 2018–2020 season data for model training and validation, and 2021 season data for model evaluation. Prior to AWS, he obtained his MCS from West Virginia University and worked as computer vision researcher at Midea. Each season consists of around 17,000 plays. She received her Ph.D.

ML 75

ML ML Machine Learning Machine Learning 75

The MLOps Blog

DECEMBER 7, 2022

2 To teach them how to use the stack considered best for them (mostly focusing on fundamentals of MLOps and AWS Sagemaker / Sagemaker Studio). 3 To redesign and rewrite the architecture as Infrastructure as Code (using AWS Cloudformation). After that, a chosen model gets deployed and used in the model pipeline.

ML 52

ML ML AWS ETL 52