Ml
Showing 20 of 56 projects
A TensorFlow library for training, serving, and interpreting decision forest models like Random Forests and Gradient Boosted Trees.
A blockchain framework for hosting and collaboratively training publicly available machine learning models with free predictions.
A machine learning integrations library for TypeDB, enabling graph algorithms and Graph Neural Networks on strongly-typed graph data.
Cleora is a fast, deterministic graph embedding engine that computes all random walks in a single matrix multiplication, requiring no GPUs or negative sampling.
An open-source MLOps framework for defining and deploying machine learning and LLM workloads across any cloud infrastructure.
An AutoML framework that generates and customizes machine learning pipelines using declarative JSON-AI syntax.
An open-source machine learning framework built in Rust for high-performance and extensible ML tasks.
An open-source machine learning framework built in Rust for high-performance and extensible ML tasks.
A vision transformer-based deep learning model for automated instance segmentation and classification of cell nuclei in histopathology images.
A tree ensemble machine learning method that delivers better results than gradient boosted decision trees on many datasets.
Ruby language bindings for the LIBSVM library, enabling support vector machine (SVM) classification and regression in Ruby.
A lightweight neural network library for Deno with CPU, GPU, and WASM backends, designed for serverless and edge environments.
A comprehensive scientific computing and AI/ML library in pure Rust, offering SciPy-compatible APIs with 10-100x performance gains.
A compact spiking neural network library built on JAX and Haiku, offering high-performance training via surrogate gradient descent and neuroevolution.
A PHP library for building predictions using linear regression with simple data fitting.
A Delphi/Pascal binding for TensorFlow and Keras that enables Pascal developers to build, train, and deploy machine learning models.
A .NET data visualization library inspired by ggplot2 for creating interactive charts in Blazor web apps and .NET applications.
A package manager for machine learning datasets and models with a CLI and self-hostable registry.
Ruby interface to LIBLINEAR for machine learning classification and regression tasks using SWIG bindings.
A fast and versatile implementation of support vector machines with integrated hyper-parameter selection and support for multiple learning scenarios.
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