Build XGBoost models with Amazon Redshift ML

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 scientists.

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Shared by AWS Machine Learning June 17, 2021

The 6 elements of the KM delivery structure

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 framework.

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Shared by Nick Milton June 17, 2021

Automate Amazon SageMaker Studio setup using AWS CDK

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 notebooks,

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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

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 operational

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Shared by AWS Machine Learning June 15, 2021