Datumbox is an open-source machine learning framework written in Java for rapid development of machine learning and statistical applications. It focuses on including many machine learning algorithms and statistical methods and on handling large datasets. The code is licensed under the Apache License, Version 2.0, and releases are available on Maven Central, including version 0.8.2.
Magenta is an open source research project exploring the role of machine learning as a tool in the creative process, focused on art and music. It includes Magenta Studio, a collection of music plugins for Ableton Live, and Magenta RealTime 2, an open model and real-time neural synthesis engine.
SimpleCV is an open source framework for building computer vision applications, providing access to libraries such as OpenCV without requiring knowledge of bit depths, file formats, color spaces or buffer management. The platform uses Python, and examples include connecting to a camera, binarizing images and drawing text.
Accord.NET is a .NET machine learning framework combined with audio and image processing libraries written in C#. It covers classification, regression, clustering, distributions, hypothesis tests and kernel methods, with imaging and signal processing components. The framework is intended for building computer vision, audition, signal processing and statistics applications, including commercial use. It offers sample applications, documentation and a wiki.
QSMM is a framework for learning finite automatons that perform goal-directed interaction with entities exhibiting deterministic or stochastic behavior. It implements the rudiments of a toolchain for working with probabilistic assembler programs, and development focus shifted to adaptive parsing and learning context-free grammars by template. It includes atd-parser and abu-parser tools.
prompts.chat is a community platform for discovering, collecting and sharing AI prompts for ChatGPT, Claude, Gemini and other models. It is free and open source, and can be self-hosted for private deployments. An MCP-first API supports searching and discovering prompts programmatically.
ML-Ops is a site about Machine Learning Operations. It covers motivation for MLOps, designing ML-powered software, the end-to-end ML workflow lifecycle, three levels of ML-based software, MLOps principles, CRISP-ML(Q), the MLOps Stack Canvas and ML model governance. It describes MLOps as aiming to unify the release cycle for machine learning and software.
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Magenta is an open source research project exploring the role of machine learning as a tool in the creative process, focused on art and music. It includes Magenta Studio, a collection of music plugins for Ableton Live, and Magenta RealTime 2, an open model and real-time neural synthesis engine.
SimpleCV is an open source framework for building computer vision applications, providing access to libraries such as OpenCV without requiring knowledge of bit depths, file formats, color spaces or buffer management. The platform uses Python, and examples include connecting to a camera, binarizing images and drawing text.
Accord.NET is a .NET machine learning framework combined with audio and image processing libraries written in C#. It covers classification, regression, clustering, distributions, hypothesis tests and kernel methods, with imaging and signal processing components. The framework is intended for building computer vision, audition, signal processing and statistics applications, including commercial use. It offers sample applications, documentation and a wiki.
QSMM is a framework for learning finite automatons that perform goal-directed interaction with entities exhibiting deterministic or stochastic behavior. It implements the rudiments of a toolchain for working with probabilistic assembler programs, and development focus shifted to adaptive parsing and learning context-free grammars by template. It includes atd-parser and abu-parser tools.
prompts.chat is a community platform for discovering, collecting and sharing AI prompts for ChatGPT, Claude, Gemini and other models. It is free and open source, and can be self-hosted for private deployments. An MCP-first API supports searching and discovering prompts programmatically.
ML-Ops is a site about Machine Learning Operations. It covers motivation for MLOps, designing ML-powered software, the end-to-end ML workflow lifecycle, three levels of ML-based software, MLOps principles, CRISP-ML(Q), the MLOps Stack Canvas and ML model governance. It describes MLOps as aiming to unify the release cycle for machine learning and software.
