ck
Collective Knowledge (CK), Collective Mind (CM/CMX) and MLPerf automations: community-driven projects to facilitate collaborative and reproducible research and to learn how to run AI, ML, and other emerging workloads more efficiently and cost-effectively across diverse models, datasets, software, and hardware using MLPerf methodology and benchmarks
active-learning-as-a-service
A scalable & efficient active learning/data selection system for everyone.
frouros
Frouros: an open-source Python library for drift detection in machine learning systems.
bentoml
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
tensorzero
TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation.
deepchecks
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
cresset
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
mosec
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
mlflow
The open source developer platform to build AI/LLM applications and models with confidence. Enhance your AI applications with end-to-end tracking, observability, and evaluations, all in one integrated platform.
kedro
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
weaviate
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
polyaxon
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
openllm
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
https://github.com/lancedb/lance
Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
https://github.com/flyteorg/flyte
Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
deeplake
Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
https://github.com/zenml-io/zenml
ZenML 🙏: MLOps for Reliable AI: from Classical AI to Agents. https://zenml.io.
https://github.com/apache/airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
state-of-open-source-ai
:closed_book: Clarity in the current fast-paced mess of Open Source innovation
https://github.com/featureform/featureform
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
argilla
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
https://github.com/apache/hamilton
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
https://github.com/superduper-io/superduper
Superduper: End-to-end framework for building custom AI applications and agents.
https://github.com/sematic-ai/sematic
An open-source ML pipeline development platform
https://github.com/polyaxon/hypertune
A library for performing hyperparameter optimization
monai-deploy
MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.
https://github.com/hongbo-miao/hongbomiao.com
A personal research and development (R&D) lab that facilitates the sharing of knowledge.
https://github.com/thebabylonai/babylog
A lightweight logger for machine learning teams to log images and predictions in production.
https://github.com/thenewflesh/hidebound
Hidebound is massive, distributed digital asset management system for ML pipelines on Kubernetes
https://github.com/neptune-ai/neptune-notebooks
📚 Jupyter Notebooks extension for versioning, managing and sharing notebook checkpoints in your machine learning and data science projects.
https://github.com/ploomber/soorgeon
Convert monolithic Jupyter notebooks 📙 into maintainable Ploomber pipelines. 📊
https://github.com/whylabs/whylogs
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
https://github.com/raptor-ml/raptor
Transform your pythonic research to an artifact that engineers can deploy easily.
https://github.com/bentoml/clip-api-service
CLIP as a service - Embed image and sentences, object recognition, visual reasoning, image classification and reverse image search
https://github.com/agnostiqhq/covalent-cloud-github-workflow
Template for integrating Covalent Cloud's high-performance computing capabilities into GitHub Workflows
https://github.com/agnostiqhq/tutorials_covalent_mlops_2022
Covalent tutorial for MLOps 2022
https://github.com/bentoml/transformers-nlp-service
Online Inference API for NLP Transformer models - summarization, text classification, sentiment analysis and more
https://github.com/adalkiran/distributed-inference
A project to demonstrate an approach to designing cross-language and distributed pipeline in deep learning/machine learning domain, using WebRTC and Redis Streams.
https://github.com/awslabs/aiops-modules
AIOps modules is a collection of reusable Infrastructure as Code (IaC) modules for Machine Learning (ML), Foundation Models (FM), Large Language Models (LLM) and GenAI development and operations on AWS
agilerl
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.
trustpy-tools
TrustPy is a production-ready Python package purpose-built for MLOps pipelines—enabling automated, interpretable analysis of model trustworthiness and predictive reliability before deployment. Available via Conda-Forge and PyPI, with full CI/CD integration and seamless compatibility across modern ML stacks.
https://github.com/amr-yasser226/customer-churn-prediction
End-to-end customer churn prediction project: dataset preparation, experiments with scikit-learn, model tracking with MLflow, data versioning (DVC), CI/CD, and deployment examples.
deeptsf
The DeepTSF time series forecasting repository developed by EPU NTUA within the DeployAI project
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning