Source: aws.amazon.com
How CyberCRX cut ML processing time from 8 days to 56 minutes with AWS Step
https://aws.amazon.com/polly/ Last December, https://aws.amazon.com/blogs/aws/step-functions-distributed-map-a-serverless-solution-for-large-scale-parallel-data-processing/ https://aws.amazon.com/step-functions, a new feature that allows you to orchestrate large-scale parallel workloads in the cloud. In addition, the new implementation with AWS Step Functions Distributed Map costs less than what it did originally.
Whenever there’s a new company or the data changes for a company, they regenerate their predictive model by processing their entire dataset. Over time, CyberGRX data scientists improve the model or add new features to it, which also requires the model to be regenerated.
And to make sure that the steps were run in parallel, he used Step Functions and the https://docs.aws.amazon.com/step-functions/latest/dg/amazon-states-language-map-state.html.
Whenever there’s a new company or the data changes for a company, they regenerate their predictive model by processing their entire dataset. Over time, CyberGRX data scientists improve the model or add new features to it, which also requires the model to be regenerated.
And to make sure that the steps were run in parallel, he used Step Functions and the https://docs.aws.amazon.com/step-functions/latest/dg/amazon-states-language-map-state.html.
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