Securing Amazon Comprehend API calls with AWS PrivateLink

Favorite Amazon Comprehend now supports Amazon Virtual Private Cloud (Amazon VPC) endpoints via AWS PrivateLink so you can securely initiate API calls to Amazon Comprehend from within your VPC and avoid using the public internet. Amazon Comprehend is a fully managed natural language processing (NLP) service that uses machine learning

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Shared by AWS Machine Learning August 11, 2020

Amazon Forecast can now use Convolutional Neural Networks (CNNs) to train forecasting models up to 2X faster with up to 30% higher accuracy

Favorite We’re excited to announce that Amazon Forecast can now use Convolutional Neural Networks (CNNs) to train forecasting models up to 2X faster with up to 30% higher accuracy. CNN algorithms are a class of neural network-based machine learning (ML) algorithms that play a vital role in Amazon.com’s demand forecasting

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Shared by AWS Machine Learning August 11, 2020

Machine learning best practices in financial services

Favorite We recently published a new whitepaper, Machine Learning Best Practices in Financial Services, that outlines security and model governance considerations for financial institutions building machine learning (ML) workflows. The whitepaper discusses common security and compliance considerations and aims to accompany a hands-on demo and workshop that walks you through

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Shared by AWS Machine Learning August 10, 2020

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

Favorite 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

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Shared by AWS Machine Learning August 5, 2020

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

Favorite 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

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Shared by AWS Machine Learning August 5, 2020

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

Favorite 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,

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Shared by AWS Machine Learning August 4, 2020