awesome-mlops

AutoGluon

Automated machine learning for image, text, tabular, time-series, and multi-modal data

AutoKeras

AutoKeras goal is to make machine learning accessible for everyone

AutoPyTorch

Automatic architecture search and hyperparameter optimization for PyTorch

AutoSKLearn

Automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator

EvalML

A library that builds, optimizes, and evaluates ML pipelines using domain-specific functions

FLAML

Finds accurate ML models automatically, efficiently and economically

Automates ML workflow, which includes automatic training and tuning of models

MindsDB

AI layer for databases that allows you to effortlessly develop, train and deploy ML models

MLBox

MLBox is a powerful Automated Machine Learning python library

Model Search

Framework that implements AutoML algorithms for model architecture search at scale

NNI

An open source AutoML toolkit for automate machine learning lifecycle

ClearML

Auto-Magical CI/CD to streamline your ML workflow

CML

Open-source library for implementing CI/CD in machine learning projects

KitOps

– Open source MLOps project that eases model handoffs between data scientist and DevOps

Monitor any cron job or scheduled task

Simple and effective cron job monitoring

Data discovery and metadata engine for improving the productivity when interacting with data

Provides open metadata management and governance capabilities to build a data catalog

CKAN

Open-source DMS (data management system) for powering data hubs and data portals

DataHub

LinkedIn's generalized metadata search & discovery tool

Magda

A federated, open-source data catalog for all your big data and small data

Metacat

Unified metadata exploration API service for Hive, RDS, Teradata, Redshift, S3 and Cassandra

A Single place to discover, collaborate and get your data right

Snorkel

A system for quickly generating training data with weak supervision

Upgini

Enriches training datasets with features from public and community shared data sources

Enables data-driven, interactive data analytics and collaborative documents

BambooLib

An intuitive GUI for Pandas DataFrames

DataPrep

Collect, clean and visualize your data in Python

Hosted Jupyter notebook service that requires no setup to use

Web-based notebook environment for interactive computing

The next-generation user interface for Project Jupyter

Jupytext

Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts

Pandas Profiling

Create HTML profiling reports from pandas DataFrame objects

The polyglot notebook with first-class Scala support

Dead simple, ultra fast storage for the hybrid Kubernetes world

BlazingSQL

A lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF

Delta Lake

Storage layer that brings scalable, ACID transactions to Apache Spark and other engines

Dolt

SQL database that you can fork, clone, branch, merge, push and pull just like a git repository

Dud

A lightweight CLI tool for versioning data alongside source code and building data pipelines

Management and versioning of datasets and machine learning models

An open source Git extension for versioning large files

Hub

A dataset format for creating, storing, and collaborating on AI datasets of any size

Intake

A lightweight set of tools for loading and sharing data in data science projects

lakeFS

Repeatable, atomic and versioned data lake on top of object storage

Marquez

Collect, aggregate, and visualize a data ecosystem's metadata

Milvus

An open source embedding vector similarity search engine powered by Faiss, NMSLIB and Annoy

Managed and distributed vector similarity search used with a lightweight SDK

Qdrant

An open source vector similarity search engine with extended filtering support

Quilt

A self-organizing data hub with S3 support

Platform to programmatically author, schedule, and monitor workflows

Azkaban

Batch workflow job scheduler created at LinkedIn to run Hadoop jobs

Dagster

A data orchestrator for machine learning, analytics, and ETL

Framework that allows for the distributed processing of large data sets across clusters

OpenRefine

Power tool for working with messy data and improving it

Unified analytics engine for large-scale data processing

Cerberus

Lightweight, extensible data validation library for Python

Cleanlab

Python library for data-centric AI and machine learning with messy, real-world data and labels

A Python data validation framework that allows to test your data against datasets

A vocabulary that allows you to annotate and validate JSON documents

TFDV

An library for exploring and validating machine learning data

SQL/drag-and-drop querying and visualisation tool based on notebooks

Dash

Analytical Web Apps for Python, R, Julia, and Jupyter

Reporting solution for power users who want to go beyond the data and dashboards of GA

Facets

Visualizations for understanding and analyzing machine learning datasets

Multi-platform open source analytics and interactive visualization web application

Lux

Fast and easy data exploration by automating the visualization and data analysis process

The simplest, fastest way to get business intelligence and analytics to everyone

Connect to any data source, easily visualize, dashboard and share your data

SolidUI

AI-generated visualization prototyping and editing platform, support 2D and 3D models

Modern, enterprise-ready business intelligence web application

Powerful and fastest growing data visualization tool used in the business intelligence industry

Alibi Detect

An open source Python library focused on outlier, adversarial and drift detection

Frouros

An open source Python library for drift detection in machine learning systems

TorchDrift

A data and concept drift library for PyTorch

Feature Engine

Feature engineering package with SKlearn like functionality

Featuretools

Python library for automated feature engineering

TSFresh

Python library for automatic extraction of relevant features from time series

Butterfree

A tool for building feature stores. Transform your raw data into beautiful features

ByteHub

An easy-to-use feature store. Optimized for time-series data

End-to-end open source feature store for machine learning

Feathr

An enterprise-grade, high performance feature store

Featureform

A Virtual Feature Store. Turn your existing data infrastructure into a feature store

A fully-managed feature platform built to orchestrate the complete lifecycle of features

Advisor

Open-source implementation of Google Vizier for hyper parameters tuning

Hyperas

A very simple wrapper for convenient hyperparameter optimization

Hyperopt

Distributed Asynchronous Hyperparameter Optimization in Python

Katib

Kubernetes-based system for hyperparameter tuning and neural architecture search

KerasTuner

Easy-to-use, scalable hyperparameter optimization framework

Open source hyperparameter optimization framework to automate hyperparameter search

Scikit Optimize

Simple and efficient library to minimize expensive and noisy black-box functions

Talos

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Python library for experiment execution and hyperparameter tuning at any scale

Knowledge Repo

Knowledge sharing platform for data scientists and other technical professions

One place for data insights so your entire team can learn from your data

aiWARE helps MLOps teams evaluate, deploy, integrate, scale & monitor ML models

Securely govern your machine learning operations with a healthy ML lifecycle

Transform ML/DL research into products. Faster

Deploys machine learning projects developed in Python, to Kubernetes

An end-to-end machine learning platform to build and deploy AI models at scale

A platform built on open source tools for data, model and pipeline management

Platform democratizing access to data and enabling enterprises to build their own path to AI

AI platform that democratizes data science and automates the end-to-end ML at scale

One place for your data science tools, apps, results, models, and knowledge

Platform for creating, optimizing, and deploying AI/ML algorithms for edge devices

envd

Machine learning development environment for data science and AI/ML engineering teams

Simplifies the workflow of federated learning anywhere at any scale

Multicloud CI/CD and MLOps platform for machine learning teams

Open source leader in AI with a mission to democratize AI for everyone

Open-source platform for developing and operating machine learning models at scale

Data science platform that automates MLOps with end-to-end machine learning pipelines

Automate your cycle of intelligence with Katonic MLOps Platform

Create and productionize data science using one easy and intuitive environment

Making deployments of ML workflows on Kubernetes simple, portable and scalable

A complete graph data science platform for very large graphs and other datasets

ML Workspace

All-in-one web-based IDE specialized for machine learning and data science

MLReef

Open source MLOps platform that helps you collaborate, reproduce and share your ML work

Deploy, connect, run, and monitor machine learning (ML) models in the enterprise and at the edge

MLOps platform that integrates open-source and proprietary tools into client-oriented systems

Simplifies and accelerates MLOps by bridging the gap between ML models and edge hardware

Combines data lineage with end-to-end pipelines on Kubernetes, engineered for the enterprise

A platform for reproducible and scalable machine learning and deep learning on kubernetes

Fully managed service that provides the ability to build, train, and deploy ML models quickly

Cloud native AI, analytic and data management platform that supports the analytics life cycle

An open-source end-to-end pipelining tool to go from laptop prototype to cloud in no time

A platform that makes it easy to track runs, visualize training, and scale hyperparameter tuning

A Cloud-native MLOps Platform over Kubernetes to simplify training and serving of ML Models

Takes you from POC to production while managing the whole model lifecycle

AIF360

A comprehensive set of fairness metrics for datasets and machine learning models

Fairlearn

A Python package to assess and improve fairness of machine learning models

Opacus

A library that enables training PyTorch models with differential privacy

TensorFlow Privacy

Library for training machine learning models with privacy for training data

Alibi

Open-source Python library enabling ML model inspection and interpretation

Captum

Model interpretability and understanding library for PyTorch

ELI5

Python package which helps to debug machine learning classifiers and explain their predictions

InterpretML

A toolkit to help understand models and enable responsible machine learning

LIME

Explaining the predictions of any machine learning classifier

Lucid

Collection of infrastructure and tools for research in neural network interpretability

SAGE

For calculating global feature importance using Shapley values

SHAP

A game theoretic approach to explain the output of any machine learning model

Aeromancy

A framework for performing reproducible AI and ML for Weights and Biases

Aim

A super-easy way to record, search and compare 1000s of ML training runs

Cascade

Library of ML-Engineering tools for rapid prototyping and experiment management

Comet

Track your datasets, code changes, experimentation history, and models

Open source experiment tracking, pipeline automation, and hyperparameter tuning

Keepsake

Version control for machine learning with support to Amazon S3 and Google Cloud Storage

Makes it easy to track the progress of a machine learning project

Open source platform for the machine learning lifecycle

ModelDB

Open source ML model versioning, metadata, and experiment management

The most lightweight experiment management tool that fits any workflow

Sacred

A tool to help you configure, organize, log and reproduce experiments

Weights and Biases

A tool for visualizing and tracking your machine learning experiments

Host your ML inference code on serverless GPUs and integrate it into your app with one line of code

Develop on serverless GPUs, deploy highly performant APIs, and rapidly prototype ML models

BentoML

Open-source platform for high-performance ML model serving

BudgetML

Deploy a ML inference service on a budget in less than 10 lines of code

Cog

Open-source tool that lets you package ML models in a standard, production-ready container

Machine learning model serving infrastructure

Host inference APIs, bulk inference and fine tune text, vision, audio and multi-modal models

Gradio

Create customizable UI components around your models

Machine learning model deployment made simple

Hydrosphere

Platform for deploying your Machine Learning to production

KFServing

Kubernetes custom resource definition for serving ML models on arbitrary frameworks

LocalAI

Drop-in replacement REST API that’s compatible with OpenAI API specifications for inferencing

Merlin

A platform for deploying and serving machine learning models

MLEM

Version and deploy your ML models following GitOps principles

Opyrator

Turns your ML code into microservices with web API, interactive GUI, and more

PredictionIO

Event collection, deployment of algorithms, evaluation, querying predictive results via APIs

Serverless platform for processing data streams in real-time with machine learning models

Rune

Provides containers to encapsulate and deploy EdgeML pipelines and applications

Take your ML projects from POC to production with maximum efficiency and minimal risk

Streamlit

Lets you create apps for your ML projects with deceptively simple Python scripts

Flexible, high-performance serving system for ML models, designed for production

TorchServe

A flexible and easy to use tool for serving PyTorch models

Triton Inference Server

Provides an optimized cloud and edge inferencing solution

Vespa

Store, search, organize and make machine-learned inferences over big data at serving time

A platform for deploying, serving, and optimizing ML models in both cloud and edge environments

Deepchecks

Open-source package for validating ML models & data, with various checks and suites

Starwhale

An MLOps/LLMOps platform for model building, evaluation, and fine-tuning

Trubrics

Validate machine learning with data science and domain expert feedback

Accelerate

A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

Provides advanced parallelism for analytics, enabling performance at scale for the tools you love

DeepSpeed

Deep learning optimization library that makes distributed training easy, efficient, and effective

Python distributed computing library for modern computer clusters

Horovod

Distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet

Distributed linear algebra framework and mathematically expressive Scala DSL

Apache Spark's scalable machine learning library

Modin

Speed up your Pandas workflows by changing a single line of code

Nebullvm

Easy-to-use library to boost AI inference

Nos

Open-source module for running AI workloads on Kubernetes in an optimized way

Petastorm

Enables single machine or distributed training and evaluation of deep learning models

Gives the ability to execute end-to-end data science and analytics pipelines entirely on GPUs

Ray

Fast and simple framework for building and running distributed applications

Apache top level project, focusing on distributed training of DL and ML models

Tpot

Automated ML tool that optimizes machine learning pipelines using genetic programming

Turns models into ML-friendly containers that run just about anywhere

Hermione

Help Data Scientists on setting up more organized codes, in a quicker and simpler way

Hydra

A framework for elegantly configuring complex applications

Koalas

Pandas API on Apache Spark. Makes data scientists more productive when interacting with big data

Ludwig

Allows users to train and test deep learning models without the need to write code

MLNotify

No need to keep checking your training, just one import line and you'll know the second it's done

Open source, low-code machine learning library in Python

Sagify

A CLI utility to train and deploy ML/DL models on AWS SageMaker

Soopervisor

Export ML projects to Kubernetes (Argo workflows), Airflow, AWS Batch, and SLURM

Soorgeon

Convert monolithic Jupyter notebooks into maintainable pipelines

TrainGenerator

A web app to generate template code for machine learning

Turi Create

Simplifies the development of custom machine learning models

Observability with customized monitoring and explainability for ML models

A free end-to-end ML observability and model monitoring platform

Evidently

Interactive reports to analyze ML models during validation or production monitoring

Monitor, explain, and analyze your AI in production

Manifold

A model-agnostic visual debugging tool for machine learning

NannyML

Algorithm capable of fully capturing the impact of data drift on performance

Netron

Visualizer for neural network, deep learning, and machine learning models

Opik

Evaluate, test, and ship LLM applications with a suite of observability tools

MLOps in a Notebook for troubleshooting and fine-tuning generative LLM, CV, and tabular models

Radicalbit

The open source solution for monitoring your AI models in production

Fully automated, enterprise-grade model observability in a self-service SaaS platform

Whylogs

The open source standard for data logging. Enables ML monitoring and observability

Yellowbrick

Visual analysis and diagnostic tools to facilitate machine learning model selection

Argo

Open source container-native workflow engine for orchestrating parallel jobs on Kubernetes

Rapidly build & deploy AI-powered workflows

Couler

Unified interface for constructing and managing workflows on different workflow engines

dstack

An open-core tool to automate data and training workflows

Easy to create concurrent, scalable, and maintainable workflows for machine learning

Hamilton

A scalable general purpose micro-framework for defining dataflows

Kale

Aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows

Kedro

Library that implements software engineering best-practice for data and ML pipelines

Luigi

Python module that helps you build complex pipelines of batch jobs

Human-friendly lib that helps scientists and engineers build and manage data science projects

MLRun

Generic mechanism for data scientists to build, run, and monitor ML tasks and pipelines

Orchest

Visual pipeline editor and workflow orchestrator with an easy to use UI and based on Kubernetes

Ploomber

Write maintainable, production-ready pipelines. Develop locally, deploy to the cloud

A workflow management system, designed for modern infrastructure

VDP

An open-source tool to seamlessly integrate AI for unstructured data into the modern data stack

A web-hosted IDE where non-technical domain experts can build task-specific AI agents

ZenML

An extensible open-source MLOps framework to create reproducible pipelines

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