2017, AWS and Cross Validation - Data Science Current

Search:

DAY

WEEK

MONTH

YEAR

Select your country:
Sign up | Log in

2017

AWS

Cross Validation

Build a crop segmentation machine learning model with Planet data and Amazon SageMaker geospatial capabilities

AWS Machine Learning Blog

SEPTEMBER 29, 2023

In late 2023, Planet announced a partnership with AWS to make its geospatial data available through Amazon SageMaker. Our results reveal that the classification from the KNN model is more accurately representative of the state of the current crop field in 2017 than the ground truth classification data from 2015.

Machine Learning

Machine Learning Machine Learning ML ML

Identifying defense coverage schemes in NFL’s Next Gen Stats

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. We perform a five-fold cross-validation to select the best model during training, and perform hyperparameter optimization to select the best settings on multiple model architecture and training parameters.

ML ML Machine Learning Machine Learning

Webinars

Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

MORE WEBINARS

Build a crop segmentation machine learning model with Planet data and Amazon SageMaker geospatial capabilities

Identifying defense coverage schemes in NFL’s Next Gen Stats

Webinars

Stay Connected