aws/sagemaker-spark
A Spark library for Amazon SageMaker.
This tool helps data scientists and machine learning engineers easily integrate their large-scale data processing workflows with Amazon SageMaker's machine learning capabilities. You can feed your Spark DataFrames into SageMaker for training using either Amazon's built-in algorithms or your own custom models, and then get predictions back on Spark DataFrames from the deployed SageMaker models. It's designed for those managing big data machine learning pipelines.
301 stars. No commits in the last 6 months.
Use this if you need to train machine learning models at scale using Amazon SageMaker directly from your Apache Spark applications, or if you want to deploy and get predictions from SageMaker models within your Spark pipelines.
Not ideal if you are not using Apache Spark for data processing, or if you prefer to manage your machine learning workflows entirely outside of the Amazon SageMaker ecosystem.
Stars
301
Forks
128
Language
Scala
License
Apache-2.0
Category
Last pushed
Mar 08, 2025
Commits (30d)
0
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