aws / sagemaker-xgboost-containerLinks
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.
☆139Updated this week
Alternatives and similar repositories for sagemaker-xgboost-container
Users that are interested in sagemaker-xgboost-container are comparing it to the libraries listed below
Sorting:
- Support code for building and running Amazon SageMaker compatible Docker containers based on the open source framework Scikit-learn (http…☆181Updated this week
- Experiment tracking and metric logging for Amazon SageMaker notebooks and model training.☆127Updated last year
- Amazon SageMaker Local Mode Examples☆259Updated 4 months ago
- ☆136Updated last year
- CLI for building Docker images in SageMaker Studio using AWS CodeBuild.☆56Updated 3 years ago
- WARNING: This package has been deprecated. Please use the SageMaker Training Toolkit for model training and the SageMaker Inference Toolk…☆186Updated 5 years ago
- Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.☆407Updated last year
- ☆145Updated 2 years ago
- Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events☆144Updated last year
- Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.☆517Updated last month
- The open source version of the Amazon SageMaker docs☆251Updated 2 years ago
- Safe blue/green deployment of Amazon SageMaker endpoints using AWS CodePipeline, CodeBuild and CodeDeploy.☆106Updated 2 years ago
- Amazon SageMaker examples for prebuilt framework mode containers, a.k.a. Script Mode, and more (BYO containers and models etc.)☆171Updated last year
- Amazon SageMaker MLOps deployment pipeline for A/B Testing of machine learning models.☆44Updated 4 years ago
- The MLOps Workload Orchestrator solution helps you streamline and enforce architecture best practices for machine learning (ML) model pro…☆155Updated 3 months ago
- Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS☆292Updated 4 months ago
- Amazon SageMaker Solution for explaining credit decisions.☆96Updated 2 years ago
- This sample demonstrates how to setup an Amazon SageMaker MLOps end-to-end pipeline for Drift detection☆62Updated last year
- Toolkit for allowing inference and serving with PyTorch on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at h…☆141Updated 11 months ago
- A collection of sample scripts to customize Amazon SageMaker Notebook Instances using Lifecycle Configurations☆430Updated last year
- MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK☆147Updated 4 months ago
- This repository contains examples of Docker images that can be used as custom images for KernelGateway Apps in SageMaker Studio☆133Updated 2 years ago
- Example templates for the delivery of custom ML solutions to production so you can get started quickly without having to make too many de…☆74Updated last year
- Managing your machine learning lifecycle with MLflow and Amazon SageMaker☆153Updated this week
- A TensorFlow Serving solution for use in SageMaker. This repo is now deprecated.☆172Updated 2 years ago
- Workshop content for applying DevOps practices to Machine Learning workloads using Amazon SageMaker☆321Updated 2 years ago
- Scale complete ML development with Amazon SageMaker Studio☆182Updated 10 months ago
- Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models.☆71Updated 5 months ago
- ☆230Updated last year
- ☆87Updated last year