Building machine learning workflows with Amazon SageMaker Processing jobs and AWS Step Functions

Favorite Machine learning (ML) workflows orchestrate and automate sequences of ML tasks, including data collection, training, testing, evaluating an ML model, and deploying the models for inference. AWS Step Functions automates and orchestrates Amazon SageMaker-related tasks in an end-to-end workflow. The AWS Step Functions Data Science Software Development Kit (SDK)

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Shared by AWS Machine Learning August 4, 2020

This month in AWS Machine Learning: July 2020 edition

Favorite Every day there is something new going on in the world of AWS Machine Learning—from launches to new use cases like posture detection to interactive trainings like the AWS Power Hour: Machine Learning on Twitch. We’re packaging some of the not-to-miss information from the ML Blog and beyond for

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Shared by AWS Machine Learning August 1, 2020

Create a multi-region Amazon Lex bot with Amazon Connect for high availability

Favorite AWS customers rely on Amazon Lex bots to power their Amazon Connect self service conversational experiences on telephone and other channels. With Amazon Lex, callers (or customers, in Amazon Connect terminology) can get their questions conveniently answered regardless of agent availability. What architecture patterns can you use to make a bot resilient

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Shared by AWS Machine Learning July 31, 2020

Simplifying application onboarding with Amazon CodeGuru Profiler

Favorite Amazon CodeGuru Profiler provides recommendations to help you continuously fine-tune your application’s performance. It does this by collecting runtime performance data from your live applications. It looks for your most expensive lines of code continuously and provides intelligent recommendations. This helps you more easily understand your applications’ runtime behavior

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Shared by AWS Machine Learning July 29, 2020