Ml
Showing 32 of 32 projects
An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
An end-to-end open source platform for machine learning with a comprehensive ecosystem of tools and libraries.
A 12-week, 26-lesson curriculum teaching classic machine learning using Scikit-learn through hands-on projects and quizzes.
A visualizer for neural network, deep learning, and machine learning models across multiple frameworks.
Jupyter notebooks with example code and exercises from the first edition of Hands-on Machine Learning with Scikit-Learn and TensorFlow.
An open-source AI engineering platform for debugging, evaluating, monitoring, and optimizing production LLM applications and machine learning models.
An open standard format for representing machine learning models to enable interoperability between frameworks.
An open-source AI memory tool that captures your screen and audio locally, enabling search and automation agents based on your computer activity.
An open-source AI memory tool that records your screen and audio locally, enabling search and automation agents based on your computer activity.
A composable, modular, and scalable machine learning toolkit for building AI platforms on Kubernetes.
A blazing-fast, lightweight deep learning inference engine from Alibaba, optimized for on-device LLMs and Edge AI.
An open-source LLMOps platform unifying gateway, observability, evaluation, optimization, and experimentation for industrial-grade LLM applications.
A research framework for fast prototyping of reinforcement learning algorithms, designed for easy experimentation and reproducibility.
An open-source, low-code Python library that automates end-to-end machine learning workflows.
An open-source, cross-platform machine learning framework for .NET developers to build, train, and deploy custom ML models.
A lightweight, modular, and scalable deep learning framework built on the original Caffe.
An open-source feature store for managing and serving machine learning features for training and online inference.
An open-source, self-hosted ML experiment tracker with a performant UI and SDK for comparing and querying training runs.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
An end-to-end framework for building custom AI applications and agents directly integrated with databases.
An open-source library for building massively scalable machine learning pipelines on Apache Spark.
An engine-agnostic deep learning framework for Java developers, providing a high-level API for model training and inference.
A collection of samples demonstrating how to use ML.NET for various machine learning tasks in .NET applications.
An open-source solution for continuous validation of machine learning models and data, from research to production.
A comprehensive collection of machine learning algorithms and mathematical utilities implemented in JavaScript for browser and Node.js.
A Scala API for Apache Beam and Google Cloud Dataflow, enabling unified batch and streaming data processing.
A curated list of libraries, tutorials, and resources for implementing machine learning in the Ruby programming language.
A curated list of awesome libraries, data sources, tutorials, and resources for machine learning using the Ruby programming language.
A Ruby library for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A Ruby gem for building LLM-powered applications with a unified interface for multiple providers, RAG systems, and AI assistants.
A Python package for concise, transparent, and accurate predictive modeling with sklearn-compatible interpretable models.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.