Customize the Amazon SageMaker XGBoost algorithm container

Favorite The built-in Amazon SageMaker XGBoost algorithm provides a managed container to run the popular XGBoost machine learning (ML) framework, with added convenience of supporting advanced training or inference features like distributed training, dataset sharding for large-scale datasets, A/B model testing, or multi-model inference endpoints. You can also extend this

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Shared by AWS Machine Learning April 6, 2022

Automatically generate model evaluation metrics using SageMaker Autopilot Model Quality Reports

Favorite Amazon SageMaker Autopilot helps you complete an end-to-end machine learning (ML) workflow by automating the steps of feature engineering, training, tuning, and deploying an ML model for inference. You provide SageMaker Autopilot with a tabular data set and a target attribute to predict. Then, SageMaker Autopilot automatically explores your

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Shared by AWS Machine Learning March 30, 2022