Protect PII using Amazon S3 Object Lambda to process and modify data during retrieval

Favorite Regulatory mandates, audit requirements, and security policies often call for data visibility and granular data control while using Amazon Simple Storage Service (Amazon S3) for shared datasets. Because data on Amazon S3 is often accessible by multiple applications and teams, fine-grained access controls should be implemented to restrict privileged

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Shared by AWS Machine Learning June 4, 2021

DeepLearning.AI, Coursera, and AWS launch the new Practical Data Science Specialization with Amazon SageMaker

Favorite Amazon Web Services (AWS), Coursera, and DeepLearning.AI are excited to announce Practical Data Science, a three-course, 10-week, hands-on specialization designed for data professionals to quickly learn the essentials of machine learning (ML) in the AWS Cloud. DeepLearning.AI was founded in 2017 by Andrew Ng, an ML and education pioneer,

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Shared by AWS Machine Learning June 2, 2021

Build reusable, serverless inference functions for your Amazon SageMaker models using AWS Lambda layers and containers

Favorite In AWS, you can host a trained model multiple ways, such as via Amazon SageMaker deployment, deploying to an Amazon Elastic Compute Cloud (Amazon EC2) instance (running a Flask + NGINX, for example), AWS Fargate, Amazon Elastic Kubernetes Service (Amazon EKS), or AWS Lambda. SageMaker provides convenient model hosting

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Shared by AWS Machine Learning June 1, 2021

Use Amazon Translate in Amazon SageMaker Notebooks

Favorite Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation in 71 languages and 4,970 language pairs. Amazon Translate is great for performing batch translation when you have large quantities of pre-existing text to translate and real-time translation when you want to deliver

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Shared by AWS Machine Learning June 1, 2021

Host multiple TensorFlow computer vision models using Amazon SageMaker multi-model endpoints

Favorite Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. SageMaker accelerates innovation within your organization by providing purpose-built tools for every step of ML development, including labeling, data preparation,

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Shared by AWS Machine Learning May 26, 2021