172 Open source projects that are alternatives of or similar to amazon-sagemaker-model-serving-using-aws-cdk

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

Public reusable components for Polyaxon

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

This code is used to build & run a Docker container for performing predictions against a Spark ML Pipeline.

Deployment template for a continuous training pipeline.

Projects developed by Domino's R&D team

[Machine Learning Engineer Basic Guide] 부스트캠프 AI Tech - Product Serving 자료

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

Operationalize a video anomaly detection model with Azure ML

Zero-config CLI for aws cdk development

Lightweight and Fast Feature Store Powered by Go (and Rust).

Serving TensorFlow models with TensorFlow Serving 📙

A project-based course on the foundations of MLOps with a focus on intuition and application.

Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.

Test Suites for Validating ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.

GitHub Action that allows you to deploy machine learning models in Azure Machine Learning.

Machine Learning Operator & Controller for Kubernetes

FakeFinder builds a modular framework for evaluating various deepfake detection models, offering a web application as well as API access for integration into existing workflows.

Docker images for fastai

MLOps template with examples for Data pipelines, ML workflow management, API development and Monitoring.

All content related to machine learning from my blog

This project provides sample codes to build a simple NFT marketplace with Amazon Managed Blockchain.

Sample code for AWS data service and ML courses on LinkedIn Learning

Notes for Machine Learning Engineering for Production (MLOps) Specialization course by DeepLearning.AI & Andrew Ng

Deploy, update, and stage your WAFs while managing them centrally via FMS.

The goal of this repository is to enable data scientists and ML engineers to develop data science use cases and making it ready for production use. This means focusing on the versioning, scalability, monitoring and engineering of the solution.

All of my recommendations for aspiring engineers in a single place, coming from various areas of interest.

A collection of localized (Korean) AWS AI/ML workshop materials for hands-on labs.

Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

CDK constructs to use OpenID Connect for authenticating your Github Action workflow with AWS IAM

A collection of WhyLogs examples in various languages

A CDK construct to deploy docker image to Amazon ECR

Combinator.ml's central repo, documentation and website

A containerized REST API around OpenAI's CLIP model.

A library for managing, validating, summarizing, and visualizing data.

The Fuzzy Labs guide to the universe of open source MLOps

🐶 Hosting your own email forwarding service on AWS and managing it with Github Actions

A set of demo of deploying a Machine Learning Model in production using various methods

MLOps workshop with Amazon SageMaker

Knativeのコンポーネントを理解しながらFaaSプラットフォームをDIYするワークショップです

A highly adaptable template for full-stack Typescript web apps.

Engine for ML/Data tracking, visualization, dashboards, and model UI for Polyaxon.

Completely Scalable FastAPI based template for Machine Learning, Deep Learning and any other software project which wants to use Fast API as an API framework.

A Python wrapper for the Chemistry Development Kit (CDK)

A generic template for building end-to-end machine learning projects

Panacloud Command Line Interface (CLI) uses the design-first approach for developing APIs. It generates Modern Multi-Tenant Serverless Cloud API infrastructure, mocks, stubs, tests, and stages using CDK. GraphQL schemas and OpenAPI specifications are used to implement the design-first approach.

GitHub Action that allows you to create or connect to your Azure Machine Learning Workspace.

AWS CDK Examples Repository

Reasonable API for serving TensorFlow models using Scala

A Hybrid Serving & Analytical Processing Database.

Hands-on demonstrations for data scientists exploring SageMaker

A collection of portable workflows, automation recipes and components for MLOps in a unified CK format. Note that this repository is outdated - please check the 2nd generation of the CK workflow automation meta-framework with portable MLOps and DevOps components here:

Source for the demo notes app in the Serverless Stack Guide

Make CloudFront resize images "on the fly" via lambda@edge, cache it and persists it in S3.

A declarative KubeFlow Management Tool

A boilerplate solution for processing image and PDF documents for regulated industries, with lineage and pipeline operations metadata services.

An AWS CDK Construct to deploy microservice infra in less than 50 lines of code.

Know How Guide and Hands on Guide for AWS

a simplified machine learning container platform that helps teams get started with an automated workflow