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Releases: awslabs/realtime-fraud-detection-with-gnn-on-dgl

v2.0.5

21 Apr 06:57
9227c06
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  • fix: add missing sagemaker:AddTags to sfn execute role
  • fix: explicitly set log bucket object ownership for S3 ACL change

v2.0.4

21 Nov 02:55
bad5114
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  • pin Neptune engine version to 1.2.0.1

v2.0.4-rc0

20 Nov 08:56
bad5114
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v2.0.4-rc0 Pre-release
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  • pin Neptune engine version to 1.2.0.1

v2.0.3

28 Aug 10:51
14bd51f
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  • fix: learning rate and epoch in training

v2.0.2

18 Aug 02:06
9338d1c
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  • feat: (experimental)SageMaker serverless Inference
  • fix: bump Lambda runtime to Nodejs 16.x and Python 3.9
  • fix: update documentdb certificate when deploying to AWS China regions

v2.0.2-rc0

15 Aug 15:45
110f877
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v2.0.2-rc0 Pre-release
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  • fix: bump Lambda runtime to Nodejs 16.x and Python 3.9
  • feat: (experimental)SageMaker serverless Inference

v2.0.1

28 Oct 08:52
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  • Fix CloudFormation deployment due to expired Api key of graphql #272

v2.0.1-rc0-rel

28 Oct 07:47
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v2.0.1-rc0-rel Pre-release
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Merge tag 'v2.0.1-rc0' into cfn-rel

v2.0.1-rc0

28 Oct 07:45
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v2.0.1-rc0 Pre-release
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chore: bump projen and version to 2.0.1

v2.0.0

13 Sep 07:28
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It’s an end-to-end solution for real-time fraud detection which leverages graph database Amazon Neptune, Amazon SageMaker and Deep Graph Library (DGL) to construct a heterogeneous graph from tabular data and train a Graph Neural Network(GNN) model to detect fraudulent transactions in the IEEE-CIS dataset.

  • model training pipeline
  • online business monitor
  • online docs