MLOps workshop with Amazon SageMaker
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Updated
Mar 4, 2024 - Jupyter Notebook
MLOps workshop with Amazon SageMaker
Sample datasets and code for operationalizing Amazon Fraud Detector using SageMaker DataWrangler, Feature Store, and Pipelines.
An end-to-end MLOps pipeline that reads data from PrestoDB to train an ML model and deploy on SageMaker for batch and realtime inference.
This solution shows how to deliver reusable and self-contained custom components to Amazon SageMaker environment using AWS Service Catalog, AWS CloudFormation, SageMaker Projects and SageMaker Pipelines.
Asset Prediction Sagemaker Pipelines Example
Build an MXNet image classification model via SageMaker Pipelines
A repo containing end to end sagemaker mlops pipeline for model building
This is a repo to store my implementation and steps using SageMaker (AWS)
A repo for setting pipeline for deploying model as sagemaker endpoint
Argo Workflows Executor Plugin for AWS Services, e.g. SageMaker Pipelines, Glue, etc.
This repository outlined how to implement MLOps practice on AWS Cloud using Amazon SageMaker.
This repo automates training of a Deep-AR algorithm using a Sagemaker pipeline.
An end-to-end example of a serverless machine learning pipeline for multiclass classification on AWS with SageMaker Pipelines, Data Wrangler, Athena and XGBoost.
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