aws-samples Goto Github PK

amazon-sagemaker-automatic-deploy-mlflow-model

amazon-sagemaker-automatic-speech-recognition

This repository describes how to build an automatic speech recognition (ASR) model using SageMaker and DeepSpeech Library.

amazon-sagemaker-autopilot-cross-account

amazon-sagemaker-autopilot-demo

Demostración de Amazon SageMaker Autopilot realizando una clasificación multiclase.

amazon-sagemaker-autopilot-feature-engineering-transformer-and-model-explainability

This repository contains sample code to generate SHAP plots out of the SageMaker autopilot.

amazon-sagemaker-aws-greengrass-custom-object-detection-model

End to end code samples for training an object detection model in Amazon SageMaker using the built-in SSD algorithm and running it on AWS IoT Greengrass.

amazon-sagemaker-aws-greengrass-custom-timeseries-forecasting

Deploy a functional, end-to-end example of training a machine learning model from IoT data

amazon-sagemaker-bert-classify-pytorch

This sample show you how to train BERT on Amazon Sagemaker using Spot instances

amazon-sagemaker-bert-finetuning-for-search

amazon-sagemaker-bert-pytorch

amazon-sagemaker-brain-segmentation

A Jupyter notebook w/ script demonstrating how to train an Apache MXNet model for Brain Segmentation on SageMaker using the OASIS dataset

amazon-sagemaker-build-a-knowledge-graph-pipeline

amazon-sagemaker-build-train-deploy

Scale complete ML development with Amazon SageMaker Studio

amazon-sagemaker-built-in-algorithms-mlops-pipeline-using-aws-cdk

MLOps Pipeline Using SageMaker & CDK, where models are from SageMaker built-in algorithms.

amazon-sagemaker-byod-template

A project template for developing BYOD docker images for use in Amazon SageMaker.

amazon-sagemaker-canvas-service-catalog

amazon-sagemaker-cdk-examples

amazon-sagemaker-cdk-examples uses AWS CDK to simplify common architectures in machine leaning operations using Sagemaker and other AWS services.

amazon-sagemaker-clarify-a2i-sample

This repository contains a sample jupyter notebook showing how to use Amazon SageMaker Clarify and Amazon A2I together in a single inference pipeline to improve transparency in machine learning solutions.

amazon-sagemaker-clarify-for-hospital-triage-nlp

amazon-sagemaker-clarify-with-sklearn

amazon-sagemaker-cloudformation-custom-resource

Deploy Amazon SageMaker notebook using CloudFormation custom resource

amazon-sagemaker-codeserver

Hosting code-server on Amazon SageMaker

amazon-sagemaker-container-with-fastai

Build a Docker container to build, train and deploy fast.ai based Deep Learning models with Amazon SageMaker

amazon-sagemaker-credit-risk-prediction-explainability-bias-detection

amazon-sagemaker-custom-container

amazon-sagemaker-custom-loss-function

This code shows how to train a model in Amazon SageMaker using a custom loss function for a binary classification problem in which the costs of different kinds of misclassification are very different.

amazon-sagemaker-custom-object-detection

This project demonstrates how you can set up a custom object detection model and track what objects were removed from a session. A session is a time window when a person is in the camera frame. This shows the basic building blocks for developing computer vision based services for tracking what things are present or not, especially when people are observed.

amazon-sagemaker-custom-recommender-system

amazon-sagemaker-cv

amazon-sagemaker-data-quality-monitor-custom-preprocessing