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This workshop shows how you can use an IP-based machine learning algorithm with Amazon SageMaker to augment and enrich findings from AWS Security services such as Amazon GuardDuty. You'll learn how to load the notebook in SageMaker, train the model, and score findings to determine abnormality of the activity.

Home Page: https://ml-threat-detection.awssecworkshops.com/

License: Apache License 2.0

Python 26.58% Shell 2.72% Jupyter Notebook 69.03% Dockerfile 1.67%

aws-ml-detection-workshop's Introduction

Using ML with SageMaker and GuardDuty to Identify Anomalous Traffic

(Formerly: Scalable, Automated Anomaly Detection with Amazon GuardDuty and SageMaker)

This workshop shows how you can use an IP-based machine learning algorithm with Amazon SageMaker to augment and enrich findings from AWS Security services such as Amazon GuardDuty. You'll learn how to load the notebook in SageMaker, train the model, and score findings to determine abnormality of the activity.

Start the workshop:

Visit the site to get started: https://ml-threat-detection.awssecworkshops.com/

License

This library is licensed under the Apache 2.0 License.

aws-ml-detection-workshop's People

Contributors

jpeddicord avatar nealjr avatar jmfuchs avatar alanmanderson avatar iugrina avatar mikewest82 avatar

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