awslabs / 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 32 (last one 2 years ago)

Stargazers 265 (1 this week)

Watchers 19 (0 this week)

Forks 146

License apache-2.0

Ranking

RepositoryStats indexes 523,840 repositories, of these awslabs/fraud-detection-using-machine-learning is ranked #135,916 (74th percentile) for total stargazers, and #113,321 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #2,934/14,471.

awslabs/fraud-detection-using-machine-learning is also tagged with popular topics, for these it's ranked: deep-learning (#2,842/7720), machine-learning (#2,689/7264)

Other Information

awslabs/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 3 open issues and 5 closed issues.

All Topics

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

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updated: 2024-05-27 @ 08:20am, id: 187254530 / R_kgDOCylHAg