Machine Learning Frameworks and Languages

Amazon SageMaker AI provides native support for popular programming languages and machine learning frameworks, empowering developers and data scientists to leverage their preferred tools and technologies. This section offers references for working with Python and R, as well as their respective software development kits (SDKs) within SageMaker AI. Additionally, it covers a wide range of machine learning and deep learning frameworks, including Apache MXNet, PyTorch, TensorFlow.

You can use Python and R natively in Amazon SageMaker notebook kernels. There are also kernels that support specific frameworks. A very popular way to get started with SageMaker AI is to use the Amazon SageMaker Python SDK. It provides open source Python APIs and containers that make it easy to train and deploy models in SageMaker AI, as well as examples for use with several different machine learning and deep learning frameworks.

For information about using specific frameworks or how to use R in SageMaker AI, see the following topics.

Languages SDKs and user guides:

• Amazon SageMaker Python SDK

• R

• API Reference

Machine learning and deep learning frameworks guides:

• Apache MXNet

• Apache Spark

• Chainer

• Hugging Face

• PyTorch

• Scikit-learn

• SparkML Serving

• TensorFlow

• Triton Inference Server