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SageMaker Spark is an open-source Spark library for Amazon SageMaker. With SageMaker Spark you construct Spark ML Pipelines using Amazon SageMaker stages. These pipelines interleave native Spark ML stages and stages that interact with SageMaker training and model hosting. With SageMaker Spark, you can train on Amazon SageMaker from Spark DataFrames using Amazon-provided ML algorithms like K-Means clustering or XGBoost, and make predictions on DataFrames against SageMaker endpoints hosting your trained models, and, if you have your own ML algorithms built into SageMaker compatible Docker containers, you can use SageMaker Spark to train and infer on DataFrames with your own algorithms -- all at Spark scale. ...
Manage an S3 website: sync, deliver via CloudFront
s3_website is a Ruby gem that automates the deployment of static websites to AWS S3 and optionally CloudFront. It handles site configuration, uploads, cache control, gzip compression, redirects, and supports Jekyll, Nanoc, and Middleman out of the box. Ideal for static site hosting without manual AWS setup.
Eclipse plug-ins that provide Prover IDE for Isabelle proof assistant, based on Isabelle/Scala framework.
Isabelle/Eclipse started as a port of Isabelle/jEdit Prover IDE to integrate with Eclipse IDE as plug-ins. The integration uses common Eclipse components to provide theory editing, correct symbols, completion assistance, prover output and other features. By building on Eclipse it inherits various IDE goodies out of the box.
This SourceForge project is used to distribute...