Fraud Detection Using Machine Learning adds improved model accuracy and flexibility
Fraud Detection Using Machine Learning is an AWS Solution that automates the detection of potentially fraudulent activity, and flags that activity for review. The solution is easy to deploy and contains an example dataset. You can also modify the solution to use your own dataset. The update improves model accuracy and now includes a model to detect anomalies in unlabeled data.
Fraud Detection Using Machine Learning is an AWS Solution that automates the detection of potentially fraudulent activity, and flags that activity for review. The solution is easy to deploy and contains an example dataset. You can also modify the solution to use your own dataset. The update improves model accuracy and now includes a model to detect anomalies in unlabeled data.
The solution deploys Amazon SageMaker, Amazon Kinesis Data Firehose, Amazon API Gateway, AWS Lambda, and Amazon S3. You can also use analytics tools such as Amazon QuickSight with the solution for visualization, reporting, ad-hoc queries, and more detailed analysis. To learn more about Fraud Detection Using Machine Learning, see the solution webpage.
Additional AWS Solutions are available on the AWS Solutions Implementations webpage, where customers can browse solutions by product category or industry to find AWS-vetted, automated, turnkey reference implementations that address specific business needs.