91 Open source projects that are alternatives of or similar to e2eml-cookiecutter

FuseML aims to provide an MLOps framework as the medium dynamically integrating together the AI/ML tools of your choice. It's an extensible tool built through collaboration, where Data Engineers and DevOps Engineers can come together and contribute with reusable integration code.

Kraken CI is a continuous integration and testing system.

Helm charts for creating reproducible and maintainable deployments of Polyaxon with Kubernetes.

Serving PyTorch models with TorchServe 🔥

ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

GitHub Action that allows you to attach, create and scale Azure Machine Learning compute resources.

Subscribe to this GitHub repo to access the latest tech talks, tech demos, learning materials & modules, and developer community updates!

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.

Monitor the stability of a Pandas or Spark dataframe ⚙︎

📒 Experiment tracking tool and model registry

mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

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

MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.

Machine Learning Operator & Controller for Kubernetes

Evaluate wandb, tensorboard, neptune, mlflow, etc

PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡

GitHub Action that allows you to register models to your Azure Machine Learning Workspace.

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.

Deployment template for a continuous training pipeline.

The collaboration workspace for Machine Learning

HI-ML toolbox for deep learning for medical imaging and Azure integration

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

Machine Learning Pipelines for Kubeflow

Polyaxon Core Client & CLI to streamline MLOps

This is an example of a Containerized Flask Application that can deploy to many target environments including: AWS, GCP and Azure.

Learn how to responsibly deliver value with ML.

A declarative KubeFlow Management Tool

A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.

The Fuzzy Labs guide to the universe of open source MLOps

Algorithm engineering is hard enough: don't spend your time with logistics. QA-Board organizes your runs and lets you visualize, compare and share results.

The MLOps Workload Orchestrator solution helps you streamline and enforce architecture best practices for machine learning (ML) model productionization. This solution is an extendable framework that provides a standard interface for managing ML pipelines for AWS ML services and third-party services.

MLOps Case Study

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

Coarse-grained lineage and tracing for machine learning pipelines.

A tool for training models to Vertex on Google Cloud Platform.

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

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

Public reusable components for Polyaxon

CartPole game by Reinforcement Learning, a journey from training to inference

Projects developed by Domino's R&D team

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

Kedro Plugin to support running pipelines on Kubernetes using Airflow.

Black-box optimization library

Slack bot for monitoring your Metaflow flows!

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

🎲 A curated list of MLOps projects, tools and resources

Portable automation meta-framework to manage, describe, connect and reuse any artifacts, scripts, tools and workflows on any platform with any software and hardware in a non-intrusive way and with minimal effort. Try it using this tutorial to modularize and automate ML Systems benchmarking from the Student Cluster Competition at SC'22:

Model Serving Made Easy

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

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

A Collection of GitHub Actions That Facilitate MLOps

Feature Store for Machine Learning

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 lightweight tool to get an AI Infrastructure Stack up in minutes not days. K3ai will take care of setup K8s for You, deploy the AI tool of your choice and even run your code on it.

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

Crane is a easy-to-use and beautiful desktop application helps you build manage your container images.

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

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:

A GitHub Action that makes it easy to use Great Expectations to validate your data pipelines in your CI workflows.