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Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK

AWS Machine Learning

In this post, we enable the provisioning of different components required for performing log analysis using Amazon SageMaker on AWS DeepRacer via AWS CDK constructs. This is where advanced log analysis comes into play. The unit tests are located in DeepRacer/test/deep_racer.test.ts

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Continuous integration and continuous delivery (CI/CD) pipeline – Using the customer’s GitHub repository enabled code versioning and automated scripts to launch pipeline deployment whenever new versions of the code are committed. Wipro has used the input filter and join functionality of SageMaker batch transformation API.

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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.