Machine Learning
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A curated list of libraries, tutorials, and resources for implementing machine learning in the Ruby programming language.
PyGAD is a Python library for building genetic algorithms and optimizing machine learning models with Keras and PyTorch support.
A simple wrapper that combines Keras and Hyperopt for convenient hyperparameter optimization in deep learning models.
Open-source robot simulation software integrated with OpenAI Gym for reinforcement learning research.
A curated collection of R tutorials, packages, and resources for Data Science, NLP, and Machine Learning.
A curated list of awesome libraries, projects, tutorials, and resources for the JAX machine learning ecosystem.
A collection of TypeScript libraries for music and art generation using pre-trained machine learning models in the browser.
A Python library for constructing differentiable convex optimization layers in PyTorch, JAX, and MLX using CVXPY.
A toolkit and library for developing, evaluating, and reproducing reinforcement learning algorithms.
.NET for Apache Spark provides high-performance .NET APIs for Apache Spark, enabling C# and F# developers to work with structured and streaming data.
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control.
A JAX-based library providing numerical differential equation solvers for ODEs, SDEs, and CDEs with autodifferentiation and GPU support.
A web/desktop application for collaborative labeling and annotation of images, text, audio, documents, and other data types.
An end-to-end Python pipeline for semantic segmentation of aerial and satellite imagery to extract features like buildings and roads.
Python library for portfolio optimization built on top of scikit-learn
A platform for developing AI bots that play Doom using visual information, designed for reinforcement learning research.
A Python framework and Rust-based distributed processing engine for stateful event and stream processing.
A collection of 30+ LaTeX drawing examples for Bayesian networks, graphical models, tensors, and academic illustrations.
A TensorFlow library for building, training, and deploying recommender system models with Keras.
A deep learning-based facial detection library for Python with facial landmark extraction.
A framework for running deep neural network models directly in web browsers using ONNX format with WebGPU, WebGL, and WebAssembly backends.
Elyra is a set of AI-centric extensions for JupyterLab that adds visual pipeline editing, batch job execution, and AI-assisted coding.
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 web-based labeling tool for creating semantic segmentation training data from 2D images and 3D point clouds.
A Julia machine learning framework providing a unified interface and meta-algorithms for over 200 models.
A recurrent neural network that generates classical music using LSTM layers and convolutional-inspired architecture.
A deep learning library in Rust featuring shape-checked tensors and neural networks with compile-time safety.
A deep learning library for Rust featuring shape-checked tensors and neural networks with compile-time safety.
A curated list of resources for adversarial machine learning, covering attacks, defenses, and research.
Automatically visualize any dataset with a single line of code, including data quality assessment and fixes.
A minimal benchmark comparing scalability, speed, and accuracy of popular open-source machine learning libraries for binary classification.
A JAX research toolkit for building, editing, and visualizing neural networks as legible, functional pytree data structures.
A Python library for probabilistic prediction using natural gradient boosting, built on scikit-learn.
A curated list of awesome Apache Spark packages, libraries, and resources for data engineers and scientists.
A high-performance Python package for fast, multi-threaded manipulation of large tabular datasets, inspired by R's data.table.
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