aws-solutions-library-samples / fraud-detection-using-machine-learning

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

Date Created 2019-05-17 (5 years ago)

Commits 37 (last one about a month ago)

Stargazers 295 (0 this week)

Watchers 33 (0 this week)

Forks 156

License apache-2.0

Ranking

RepositoryStats indexes 584,353 repositories, of these aws-solutions-library-samples/fraud-detection-using-machine-learning is ranked #134,714 (77th percentile) for total stargazers, and #65,878 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #2,977/17,098.

aws-solutions-library-samples/fraud-detection-using-machine-learning is also tagged with popular topics, for these it's ranked: deep-learning (#2,835/8389), machine-learning (#2,690/7926)

Other Information

aws-solutions-library-samples/fraud-detection-using-machine-learning has 1 open pull request on Github, 2 pull requests have been merged over the lifetime of the repository.

Github issues are enabled, there are 4 open issues and 5 closed issues.

Homepage URL: https://aws.amazon.com/solutions/guidance/fraud-detection-using-machine-learning-on-aws/

All Topics

xgboost sagemaker aws-sagemaker deep-learning fraud-detection machine-learning sagemaker-example

Star History

Github stargazers over time

Watcher History

Github watchers over time, collection started in '23

Recent Commit History

5 commits on the default branch (master) since jan '22

Yearly Commits

Commits to the default branch (master) per year

Issue History

Languages

The primary language is Jupyter Notebook but there's also others...

updated: 2024-11-20 @ 12:44pm, id: 187254530 / R_kgDOCylHAg