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Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

Additionally, we won’t be able to make an informed decision post-analysis of those insights prior to building the ML models. This solution can accelerate accurate and timely inspection of data and model quality checks, and facilitate the productivity of distinguished data and ML teams across your organization. Overview of solution.

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

By the end of the consulting engagement, the team had implemented the following architecture that effectively addressed the core requirements of the customer team, including: Code Sharing – SageMaker notebooks enable data scientists to experiment and share code with other team members.