ColossalAI - An integrated large-scale model training system with efficient parallelization techniques.
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Jax - Autograd and XLA for high-performance machine learning research.
Kedro - Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code.
Keras - Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow.
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
MegEngine - MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.
metric-learn - Metric Learning Algorithms in Python.
MindSpore - MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
Oneflow - OneFlow is a performance-centered and open-source deep learning framework.
PaddlePaddle - Machine Learning Framework from Industrial Practice.
PyTorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration.
PyTorchLightning - The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
XGBoost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library.
Kedro-Viz - Kedro-Viz is an interactive development tool for building data science pipelines with Kedro. Kedro-Viz also allows users to view and compare different runs in the Kedro project.
LabNotebook - LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments.
Visualization
Maniford - A model-agnostic visual debugging tool for machine learning.
netron - Visualizer for neural network, deep learning, and machine learning models.
OpenOps - Bring multiple data streams into one dashboard.
TensorSpace - Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js.
dtreeviz - A python library for decision tree visualization and model interpretation.
Zetane Viewer - ML models and internal tensors 3D visualizer.
Model
Model Management
dvc - Data Version Control | Git for Data & Models | ML Experiments Management
ModelDB - Open Source ML Model Versioning, Metadata, and Experiment Management
MLEM - A tool to package, serve, and deploy any ML model on any platform.
ormb - Docker for Your ML/DL Models Based on OCI Artifacts
Pretrained Model
HuggingFace - State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
PaddleNLP - Easy-to-use and Fast NLP library with awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications.
TensorFlow Model Optimization - A suite of tools that users, both novice and advanced, can use to optimize machine learning models for deployment and execution.
TNN - A uniform deep learning inference framework for mobile, desktop and server.
Observability
Deepchecks - Tests for Continuous Validation of ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.
Evidently - Evaluate and monitor ML models from validation to production.
Volcano - A Cloud Native Batch System (Project under CNCF).
Yunikorn - Light-weight, universal resource scheduler for container orchestrator systems.
LLMOps
deeplake - Stream large multimodal datasets to achieve near 100% GPU utilization. Query, visualize, & version control data. Access data w/o the need to recompute the embeddings for the model finetuning.
langchain - Building applications with LLMs through composability
Chocolate - A fully decentralized hyperparameter optimization framework.
Dragonfly - An open source python library for scalable Bayesian optimisation.
Determined - scalable deep learning training platform with integrated hyperparameter tuning support; includes Hyperband, PBT, and other search methods.
DEvol (DeepEvolution) - a basic proof of concept for genetic architecture search in Keras.
EvalML - An open source python library for AutoML.
FEDOT - AutoML framework for the design of composite pipelines.
learn2learn - PyTorch Meta-learning Framework for Researchers.
Ludwig - a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
MOE - a global, black box optimization engine for real world metric optimization by Yelp.
Model Search - a framework that implements AutoML algorithms for model architecture search at scale.
NASGym - a proof-of-concept OpenAI Gym environment for Neural Architecture Search (NAS).
NNI - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Vald - A Highly Scalable Distributed Vector Search Engine
Vearch - A distributed system for embedding-based vector retrieval
Weaviate - Weaviate is an open source vector search engine that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
Federated ML
FATE - An Industrial Grade Federated Learning Framework
FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation.
Harmonia - Harmonia is an open-source project aiming at developing systems/infrastructures and libraries to ease the adoption of federated learning (abbreviated to FL) for researches and production usage.
ArtiVC - A version control system to manage large files.
Lake is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
JuiceFS - A distributed POSIX file system built on top of Redis and S3.
LakeFS - Git-like capabilities for your object storage.
Data Transformation
Data Tracking
Piperider - A CLI tool that allows you to build data profiles and write assertion tests for easily evaluating and tracking your data's reliability over time.
LUX - A Python library that facilitates fast and easy data exploration by automating the visualization and data analysis process.
Feature Engineering
Featureform - The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
FeatureTools - An open source python framework for automated feature engineering
Data/Feature enrichment
Upgini - Free automated data & feature enrichment library for machine learning: automatically searches through thousands of ready-to-use features from public and community shared data sources and enriches your training dataset with only the accuracy improving features
Feast - An open source feature store for machine learning.
Performance
ML Compiler
ONNX-MLIR - Compiler technology to transform a valid Open Neural Network Exchange (ONNX) graph into code that implements the graph with minimum runtime support.
TVM - Open deep learning compiler stack for cpu, gpu and specialized accelerators
Profiling
scalene - a high-performance, high-precision CPU, GPU, and memory profiler for Python
Awesome Lists
Awesome Argo - A curated list of awesome projects and resources related to Argo
Awesome AutoDL - Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
Awesome AutoML - Curating a list of AutoML-related research, tools, projects and other resources
Awesome AutoML Papers - A curated list of automated machine learning papers, articles, tutorials, slides and projects
Awesome Federated Learning - A curated list of federated learning publications, re-organized from Arxiv (mostly)
Awesome Open MLOps - This is the Fuzzy Labs guide to the universe of free and open source MLOps tools.
Awesome Production Machine Learning - A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Awesome Tensor Compilers - A list of awesome compiler projects and papers for tensor computation and deep learning.
- Run VS Code on any machine anywhere and access it in the browser.
- OS-agnostic, system-level binary package manager and ecosystem.
- Moby is an open-source project created by Docker to enable and accelerate software containerization.
- 🏕️ Reproducible development environment for AI/ML.
- The Jupyter notebook is a web-based notebook environment for interactive computing.
- Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler.
- A fast open framework for deep learning.
- An integrated large-scale model training system with efficient parallelization techniques.
- DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
- Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
- Autograd and XLA for high-performance machine learning research.
- Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code.
- Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow.
- A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
- MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.
- Metric Learning Algorithms in Python.
- MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
- OneFlow is a performance-centered and open-source deep learning framework.
- Machine Learning Framework from Industrial Practice.
- Tensors and Dynamic neural networks in Python with strong GPU acceleration.
- The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
- Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library.
- Machine Learning in Python.
- An Open Source Machine Learning Framework for Everyone.
- A minimalist neural network library optimized for sparse data and single machine environments.
- an easy-to-use and performant open-source experiment tracker.
- Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
- Experiment tracking, ML developer tools.
- Machine Learning automation and tracking.
- Kedro-Viz is an interactive development tool for building data science pipelines with Kedro. Kedro-Viz also allows users to view and compare different runs in the Kedro project.
- LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
- Sacred is a tool to help you configure, organize, log and reproduce experiments.
- A model-agnostic visual debugging tool for machine learning.
- Visualizer for neural network, deep learning, and machine learning models.
- Bring multiple data streams into one dashboard.
- TensorFlow's Visualization Toolkit.
- Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js.
- A python library for decision tree visualization and model interpretation.
- ML models and internal tensors 3D visualizer.
- Data Version Control | Git for Data & Models | ML Experiments Management
- Open Source ML Model Versioning, Metadata, and Experiment Management
- A tool to package, serve, and deploy any ML model on any platform.
- Docker for Your ML/DL Models Based on OCI Artifacts
- State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
- Easy-to-use and Fast NLP library with awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications.
- PyTorch image models, scripts, pretrained weights.
- A library for transfer learning by reusing parts of TensorFlow models.
- The Unified Model Serving Framework
- Open source platform for deploying machine learning models in production.
- Policy-driven Machine Learning Model Server.
- A machine learning model serving framework with dynamic batching and pipelined stages, provides an easy-to-use Python interface.
- Multi Model Server is a tool for serving neural net models for inference.
- A uniform interface to run deep learning models from multiple frameworks
- Python + Inference - Model Deployment library in Python. Simplest model inference server ever.
- Boosting your Web Services of Deep Learning Applications.
- A flexible, high-performance serving system for machine learning models.
- Serve, optimize and scale PyTorch models in production
- The Triton Inference Server provides an optimized cloud and edge inferencing solution.
- MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
- Real-time inference for Stable Diffusion - 0.88s latency. Covers AITemplate, nvFuser, TensorRT, FlashAttention.
- FeatherCNN is a high performance inference engine for convolutional neural networks.
- A library for high performance deep learning inference on NVIDIA GPUs.
- ncnn is a high-performance neural network inference framework optimized for the mobile platform.
- use AutoML to do model compression.
- A suite of tools that users, both novice and advanced, can use to optimize machine learning models for deployment and execution.
- A uniform deep learning inference framework for mobile, desktop and server.
- Tests for Continuous Validation of ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.
- Evaluate and monitor ML models from validation to production.
- Always know what to expect from your data.
- The open standard for data logging
- Open source platform for the machine learning lifecycle.
- ModelFox is a platform for managing and deploying machine learning models.
- Standardized Serverless ML Inference Platform on Kubernetes
- Machine Learning Toolkit for Kubernetes.
- Resource scheduling and cluster management for AI.
- Machine Learning Management & Orchestration Platform.
- An effortless infrastructure for machine learning built on the top of Kubernetes.
- An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
- A platform to programmatically author, schedule and monitor workflows.
- An Open-Source Platform for Production Data Science
- Workflow engine for Kubernetes.
- Kubernetes-native workflow automation platform for complex, mission-critical data and ML processes at scale.
- Machine Learning Pipelines for Kubeflow.
- Build and manage real-life data science projects with ease!
- The fastest way to build data pipelines. Develop iteratively, deploy anywhere.
- The easiest way to automate your data.
- An open-source unstructured data ETL tool to streamline the end-to-end unstructured data processing pipeline.
- MLOps framework to create reproducible pipelines.
- Kubernetes-native Job Queueing.
- A Highly Scalable Workload Manager.
- A Cloud Native Batch System (Project under CNCF).
- Light-weight, universal resource scheduler for container orchestrator systems.
- Stream large multimodal datasets to achieve near 100% GPU utilization. Query, visualize, & version control data. Access data w/o the need to recompute the embeddings for the model finetuning.
- Building applications with LLMs through composability
- Tensorflow package for AdaNet.
- open-source implementation of Google Vizier for hyper parameters tuning.
- a platform for Neural Network Search (NAS) that allows you to generate efficient deep networks for your applications.
- An automatic ML model optimization tool.
- A framework to find the best performing AI/ML model for any AI problem.
- An autoML framework & toolkit for machine learning on graphs
- AutoML for Image, Text, and Tabular Data.
- Provide an input CSV and a target field to predict, generate a model + code to run it.
- AutoML library for deep learning.
- Automatic architecture search and hyperparameter optimization for PyTorch.
- an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
- hyperparameter search for Weka.
- A fully decentralized hyperparameter optimization framework.
- An open source python library for scalable Bayesian optimisation.
- scalable deep learning training platform with integrated hyperparameter tuning support; includes Hyperband, PBT, and other search methods.
- a basic proof of concept for genetic architecture search in Keras.
- An open source python library for AutoML.
- AutoML framework for the design of composite pipelines.
- Fast and lightweight AutoML (paper).
- A hyperparameter optimization framework, inspired by Optuna.
- a framework for distributed hyperparameter optimization.
- a library for hyperparameter optimization and black box optimization benchmarks.
- open source code for tuning hyperparams with Hyperband.
- A General Automated Machine Learning Framework.
- Distributed Asynchronous Hyperparameter Optimization in Python.
- A toolset for black-box hyperparameter optimisation.
- Katib is a Kubernetes-native project for automated machine learning (AutoML).
- Hyperparameter tuning for humans.
- PyTorch Meta-learning Framework for Researchers.
- a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
- a global, black box optimization engine for real world metric optimization by Yelp.
- a framework that implements AutoML algorithms for model architecture search at scale.
- a proof-of-concept OpenAI Gym environment for Neural Architecture Search (NAS).
- An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
- A hyperparameter optimization framework.
- An open-source, low-code machine learning library in Python that automates machine learning workflows.
- Scalable Hyperparameter Tuning.
- Bayesian optimization in high-dimensions via random embedding.
- a Robust Bayesian Optimization framework.
- Sequential model-based optimization with a
- a software package to perform Bayesian optimization.
- one of the very first AutoML methods and open-source software packages.
- A Meta-Learning library for PyTorch.
- an AutoML algorithm tool chain by Huawei Noah's Arb Lab.
- An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.
- Build multimodal AI services via cloud native technologies · Neural Search · Generative AI · Cloud Native
- Tensor search for humans.
- Vector database for scalable similarity search and AI applications.
- Vector Search Engine and Database for the next generation of AI applications. Also available in the cloud
- Build AI-powered semantic search applications
- A Highly Scalable Distributed Vector Search Engine
- A distributed system for embedding-based vector retrieval
- Weaviate is an open source vector search engine that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
- An Industrial Grade Federated Learning Framework
- The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation.
- A Friendly Federated Learning Framework
- Harmonia is an open-source project aiming at developing systems/infrastructures and libraries to ease the adoption of federated learning (abbreviated to FL) for researches and production usage.
- A framework for implementing federated learning
- A version control system to manage large files. Lake is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
- Git for Data.
- Storage layer that brings scalable, ACID transactions to Apache Spark and other engines.
- Pachyderm is a version control system for data.
- A self-organizing data hub for S3.
- A distributed POSIX file system built on top of Redis and S3.
- Git-like capabilities for your object storage.
- A CLI tool that allows you to build data profiles and write assertion tests for easily evaluating and tracking your data's reliability over time.
- A Python library that facilitates fast and easy data exploration by automating the visualization and data analysis process.
- The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
- An open source python framework for automated feature engineering
- Free automated data & feature enrichment library for machine learning: automatically searches through thousands of ready-to-use features from public and community shared data sources and enriches your training dataset with only the accuracy improving features
- An open source feature store for machine learning.
- Compiler technology to transform a valid Open Neural Network Exchange (ONNX) graph into code that implements the graph with minimum runtime support.
- Open deep learning compiler stack for cpu, gpu and specialized accelerators
- a high-performance, high-precision CPU, GPU, and memory profiler for Python
- A curated list of awesome projects and resources related to Argo
- Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
- Curating a list of AutoML-related research, tools, projects and other resources
- A curated list of automated machine learning papers, articles, tutorials, slides and projects
- A curated list of federated learning publications, re-organized from Arxiv (mostly)
- This is the Fuzzy Labs guide to the universe of free and open source MLOps tools.
- A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
- A list of awesome compiler projects and papers for tensor computation and deep learning.
- A curated list of awesome MLOps tools.
- An awesome list of references for MLOps - Machine Learning Operations
