A library for training and deploying machine learning models on Amazon SageMaker
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Updated
May 24, 2024 - Python
A library for training and deploying machine learning models on Amazon SageMaker
Probabilistic time series modeling in Python
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
Toolkit for running TensorFlow training scripts on SageMaker. Dockerfiles used for building SageMaker TensorFlow Containers are at https://github.com/aws/deep-learning-containers.
Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
Amazon SageMaker Debugger provides functionality to save tensors during training of machine learning jobs and analyze those tensors
Sagemaker pipeline for AWS Summit New York
LLMs and Machine Learning done easily
This is the Docker container based on open source framework XGBoost (https://xgboost.readthedocs.io/en/latest/) to allow customers use their own XGBoost scripts in SageMaker.
Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events
Toolkit for running MXNet training scripts on SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.com/aws/deep-learning-containers.
Amazon SageMaker Local Mode Examples
3D Dense Connected Convolutional Network (3D-DenseNet for action recognition)
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
Training deep learning models on AWS and GCP instances
Write local debuggable Python which traverses your powerful remote infra. Deploy as-is. Unobtrusive, unopinionated, PyTorch-like APIs.
ACK service controller for Amazon SageMaker
This sample demonstrates how to setup an Amazon SageMaker MLOps end-to-end pipeline for Drift detection
Add a description, image, and links to the sagemaker topic page so that developers can more easily learn about it.
To associate your repository with the sagemaker topic, visit your repo's landing page and select "manage topics."