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Metadata store for Production ML

DagsHub client libraries

Monai Deploy ⭐ 87

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

Saturn accelerates the training of large-scale deep learning models with a novel joint optimization approach.

Awesome Mlsecops ⭐ 86

A curated list of MLSecOps tools, articles and other resources on security applied to Machine Learning and MLOps systems.

Dstoolkit Mlops Base ⭐ 86

Support ML teams to accelerate their model deployment to production leveraging Azure

Benderopt ⭐ 85

Black-box optimization library

Kamonohashi ⭐ 85

AI開発プラットフォームKAMONOHASHI

The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML 🌸

Ml Template Azure ⭐ 82

Template for getting started with automated ML Ops on Azure Machine Learning

Inferoxy ⭐ 80

Service for quick deploying and using dockerized Computer Vision models

Ai Privacy Toolkit ⭐ 79

A toolkit for tools and techniques related to the privacy and compliance of AI models.

Genai Stack ⭐ 77

An End to End GenAI Framework

Fasttrackml ⭐ 77

Experiment tracking server focused on speed and scalability

Semantic Segmentation Ml Pipeline ⭐ 77

Mlops E2e ⭐ 76

MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK

Chassis turns machine learning models into portable container images that can run just about anywhere.

The repository contains a list of projects which I will work on while learning and implementing MLOps.

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

Monai Deploy App Sdk ⭐ 74

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

Soorgeon ⭐ 73

Convert monolithic Jupyter notebooks 📙 into maintainable Ploomber pipelines. 📊

Fai Model ⭐ 71

FriendliAI Model Hub

Fsdl Text Recognizer 2022 ⭐ 71

Source of the FSDL 2022 labs, which are at https://github.com/full-stack-deep-learning/fsdl-t

Qgate Model ⭐ 70

The machine learning meta-model with synthetic data (useful for MLOps/feature store), part of the quality gateway concept.

Oomstore ⭐ 70

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

Mlops.net ⭐ 69

A machine learning model operations and management tool for ML.NET

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.

Mlopstemplate ⭐ 68

Providing tools and templates to facilitate modern MLOps practices

Great_expectations_action ⭐ 68

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

Amazon Web Services Operator Interface

MLOps Python Library

Cinnamon ⭐ 66

CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system

Minimalistic ML-models auto deployment tool

Platform for a hybrid execution of ML workflows that transparently integrates local and remote runtimes

Polyaxon Examples ⭐ 65

Code for tutorials and examples

Llmops Promptflow Template ⭐ 65

LLMOps with Prompt Flow is a "LLMOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.

Beneath is a serverless real-time data platform ⚡️

Awesome Ai Safety ⭐ 64

A curated list of papers & technical articles on AI Quality & Safety 📚

Managing the lifecycle of machine learning to support scalability, impact, collaboration, compliance and sharing.

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.

Examples ⭐ 60

📝 Examples of how to use Neptune for different use cases and with various MLOps tools

Hypertune ⭐ 60

A library for performing hyperparameter optimization

Truss Examples ⭐ 60

Examples of models deployable with Truss

Haystack Core Integrations ⭐ 60

Additional packages (components, document stores and the likes) to extend the capabilities of Haystack version 2.0 and onwards

A declarative KubeFlow Management Tool

Domino Research ⭐ 59

Projects developed by Domino's R&D team

Reproducible Data Science ⭐ 58

Tutorials on creating a reproducible and maintainable data science project

Dstoolkit Mlops Databricks ⭐ 58

ML Ops Accelerator: Databricks & Azure Machine Learning Unification

Mlops Templates ⭐ 57

Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.

Pipertool ⭐ 56

Platform for data science and machine learning prototyping. Developed by Tatradev.com

DataOps framework for Machine Learning projects.

Mlops Hf Tf Vision Models ⭐ 54

MLOps for Vision Models (TensorFlow) from 🤗 Transformers with TensorFlow Extended (TFX)

Qgate Sln Mlrun ⭐ 53

The quality gate for testing MLRun/Iguazio solution.

Vetiver Python ⭐ 53

Version, share, deploy, and monitor models.

Aws Mlops Handson ⭐ 52

This repository provides a comprehensive ML infrastructure for CTR prediction, focusing on AWS services and offering practical learning experience for MLOps.

a Wide Shelf for AI and Data Science | Resources 🍔

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.

Mnist Mlops Learning ⭐ 51

In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits

Cluster Installer ⭐ 51

Install a Paperspace compute cluster anywhere

Quick Notes For Ml Ds ⭐ 49

It contains interview preparation notes provided by iNeuron, important links, MLOps resources

Build And Deploy Real Time Feature Pipeline ⭐ 45

Develop and deploy a real-time feature pipeline in Python, using Bytewax 🐝 and Hopsworks Feature Store.

Azure Databricks Mlops Mlflow ⭐ 44

Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.

Serving Pytorch Models ⭐ 43

Serving PyTorch models with TorchServe 🔥

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

Terraform Aws Metaflow ⭐ 43

Deploy production-grade Metaflow cloud infrastructure on AWS

Kedro Kubeflow ⭐ 42

Kedro Plugin to support running workflows on Kubeflow Pipelines

Cuttle Cli ⭐ 42

Cuttle automates the transformation of your Python notebook into deployment-ready projects (API, ML pipeline, or just a Python script)

Bert As A Service_tfx ⭐ 42

End-to-end pipeline with TFX to train and deploy a BERT model for sentiment analysis.

Sqlite Ml ⭐ 41

An SQLite extension for machine learning

Waterdip ⭐ 40

Open-source ML Observability Platform

Www Project Machine Learning Security Top 10 ⭐ 39

OWASP Machine Learning Security Top 10 Project

Ml_exp_tracking_benchmark ⭐ 38

Evaluate wandb, tensorboard, neptune, mlflow, etc

Amazon Sagemaker Model Serving Using Aws Cdk ⭐ 38

This repository provides AI/ML service(MachineLearning model serving) modernization solution using Amazon SageMaker, AWS CDK, and AWS Serverless services.

Ml_observability_course ⭐ 38

Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.

Ai On Openshift ⭐ 38

AI-on-OpenShift website source code

Aimodelshare ⭐ 38

Serving Tensorflow Models ⭐ 37

Serving TensorFlow models with TensorFlow Serving 📙

Mlops Template ⭐ 37

A cloud-agnostic ML Platform that will enable Data Scientists to run multiple experiments, perform hyper parameter optimization, evaluate results and serve models (batch/realtime) while still maintaining a uniform development UX across cloud environments

Deploy and Monitor ML Model in Any Cloud

Easiest way to use AI models without coding (Web UI & API support)

Python client for Kolena's machine learning testing platform

PyJaws: A Pythonic Way to Define Databricks Jobs and Workflows

Unified storage framework for the entire machine learning lifecycle

A minimalistic and pluggable machine learning platform for Kubernetes.

⭐ Serve ML models. Simple. Light. 🚀

A Data Centric annotation tool for your Named Entity Recognition projects

Data Engineering And Dataops ⭐ 34

Duke MIDS: Data Engineering and DataOps Course

Ab Testing In Ml ⭐ 34

Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.

Serving Machine Learning Models ⭐ 33

This repository contains instructions, template source code and examples on how to serve/deploy machine learning models using various frameworks and applications such as Docker, Flask, FastAPI, BentoML, Streamlit, MLflow and even code on how to deploy your machine learning model as an android app.

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

niceML 🍦 is a Python-based MLOps framework designed to streamline the development and maintenance of machine learning projects, offering efficient and scalable pipelines using TensorFlow and Dagster.

Fakefinder ⭐ 32

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.

Modsysml ⭐ 32

Model management toolkit for continuous model improvement. Evaluate and compare LLM outputs, test quality, catch regressions and automate.

Tiny configuration for Triton Inference Server

Metaflow Tools ⭐ 31

Tools and utilities for operating Metaflow in production

Data Machinelearning The Boring Way ⭐ 31

Build & Learn Data Engineering,Machine Learning over Kubernetes. No Shortcut approach.

Mlops_wspycon2023 ⭐ 31

MLOps Workshop using Weights and Bias (Wandb) and Github Actions.

Neptune Notebooks ⭐ 31

📚 Jupyter Notebooks extension for versioning, managing and sharing notebook checkpoints in your machine learning and data science projects.

Allainews_sources ⭐ 31

A list of online news & info sources in the AI/ML/Data Science space

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