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Machine learning news and insights

Safely deploying and monitoring Amazon SageMaker endpoints with AWS CodePipeline and AWS CodeDeploy

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As machine learning (ML) applications become more popular, customers are looking to streamline the process for developing, deploying, and continuously improving models. To reliably increase the frequency and quality of this cycle, customers are turning to ML operations (MLOps), which is the discipline of bringing continuous delivery principles and practices to the data science team. […]

Deploying your own data processing code in an Amazon SageMaker Autopilot inference pipeline

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The machine learning (ML) model-building process requires data scientists to manually prepare data features, select an appropriate algorithm, and optimize its model parameters. It involves a lot of effort and expertise. Amazon SageMaker Autopilot removes the heavy lifting required by this ML process. It inspects your dataset, generates several ML pipelines, and compares their performance […]

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

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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) is an open-source library that allows […]


Improving speech-to-text transcripts from Amazon Transcribe using custom vocabularies and Amazon Augmented AI

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Businesses and organizations are increasingly using video and audio content for a variety of functions, such as advertising, customer service, media post-production, employee training, and education. As the volume of multimedia content generated by these activities proliferates, businesses are demanding high-quality transcripts of video and audio to organize files, enable text queries, and improve accessibility […]




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

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AWS customers rely on Amazon Lex bots to power their Amazon Connect self service conversational experiences on telephone and other channels. With 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 to service availability issues? In this post, we describe a […]



Simplifying application onboarding with Amazon CodeGuru Profiler

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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 so you can optimize their performance, […]



Import AI 207: Counter AI; Nixon’s deepfaked moon speech; and the future of AI-driven negotiation 

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WordCraft: RL + Language…Want smarter machines? Teach them alchemy (?)…Researchers with UCL and the University of Oxford have built WordCraft, an RL-based environment for testing out agents that need to use language to reason their way through the world. The RL environment is a simplified text-only version of the game Little Alchemy 2, where you craft objects by combining other...