Human-in-the-loop review of model explanations with Amazon SageMaker Clarify and Amazon A2I

Favorite Domain experts are increasingly using machine learning (ML) to make faster decisions that lead to better customer outcomes across industries including healthcare, financial services, and many more. ML can provide higher accuracy at lower cost, whereas expert oversight can ensure validation and continuous improvement of sensitive applications like disease

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Shared by AWS Machine Learning June 7, 2021

KM "What’s in it for me" for the knowledge worker

Favorite What’s in it for the Knowledge worker, when you introduce Knowledge Management to an organisation?  This is a crucial question you need to answer. Luckily it’s an easy one to answer as well. We have already discussed on this blog about the main stakeholder groupings for Knowledge management including the

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Shared by Nick Milton June 7, 2021

Build regression models with Amazon Redshift ML

Favorite With the rapid growth of data, many organizations are finding it difficult to analyze their large datasets to gain insights. As businesses rely more and more on automation algorithms, machine learning (ML) has become a necessity to stay ahead of the competition. Amazon Redshift, a fast, fully managed, widely

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Shared by AWS Machine Learning June 4, 2021

Build an Automatic Inventory Solution with public datasets and Amazon Rekognition Custom Labels

Favorite Inventorying store items is a general demand for retail stores and supermarkets. This is usually performed manually by counting items and visually checking the correct placement. Tracking changes in inventory helps business owners evaluate performance of each product, validate correct placement, and set future restocking plans. With the cloud

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Shared by AWS Machine Learning June 4, 2021

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