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
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/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
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.
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.
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
https://github.com/bentoml/transformers-nlp-service
Online Inference API for NLP Transformer models - summarization, text classification, sentiment analysis and more
agilerl
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.