Build accurate ML training datasets using point-in-time queries with Amazon SageMaker Feature Store and Apache Spark

Favorite This post is co-written with Raphey Holmes, Software Engineering Manager, and Jason Mackay, Principal Software Development Engineer, at GoDaddy. GoDaddy is the world’s largest services platform for entrepreneurs around the globe, empowering their worldwide community of over 20 million customers—and entrepreneurs everywhere—by giving them all the help and tools

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Shared by AWS Machine Learning June 22, 2021

7 cultural barriers to KM, and how to break them

Favorite There are many cultural barriers to Knowledge Management implementation, and all of them can be broken Break Through by Joel Bombardier on Flickr There are several cultural elements that can stand in the way of successful Knowledge Management. Some of these barriers are listed below, with thoughts on how

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Shared by Nick Milton June 21, 2021

Build XGBoost models with Amazon Redshift ML

Favorite Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. In previous posts, we demonstrated how customers can use the automatic model training capability of Amazon Redshift to train their classification and regression models. Redshift ML provides several capabilities for data

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Shared by AWS Machine Learning June 17, 2021

The 6 elements of the KM delivery structure

Favorite What’s the most effective delivery structure for KM? We discuss this below. We recommend six components to the knowledge management delivery and reporting structure, shown here. 1. In the centre is the Chief Knowledge Officer, or head of Knowledge Management; accountable for delivering, maintaining and continually improving the KM

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Shared by Nick Milton June 17, 2021

Automate Amazon SageMaker Studio setup using AWS CDK

Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). Studio provides a single web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. You can quickly upload data, create new

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Shared by AWS Machine Learning June 16, 2021

Connect to your Amazon CloudWatch data to detect anomalies and diagnose their root cause using Amazon Lookout for Metrics

Favorite Amazon Lookout for Metrics uses machine learning (ML) to automatically detect and diagnose anomalies (outliers from the norm) without requiring any prior ML experience. Amazon CloudWatch provides you with actionable insights to monitor your applications, respond to system-wide performance changes, optimize resource utilization, and get a unified view of

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Shared by AWS Machine Learning June 15, 2021