Ml
Showing 36 of 72 projects
Framework and Library for Distributed Online Machine Learning
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.
A comprehensive scientific computing and AI/ML library in pure Rust, offering SciPy-compatible APIs with 10-100x performance gains.
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 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.
A Ruby client library for interacting with the Qdrant vector search database API.
A Ruby client library for interacting with the Weaviate vector search database API.
🕶️ Adds chat auto-clear functionality to ChatGPT for more privacy
Sample code demonstrating Core ML integration with ResNet50 and custom models converted via coremltools.
A Rust library for implementing Self-Organizing Maps (SOM) with customizable training and serialization.
A Ruby client library for interacting with the Milvus vector database API.
A thread-safe vector database for model inference built on LMDB.
A Swift library for building predictions using linear regression with simple API and statistical insights.
A Torch-like deep learning framework for JavaScript with direct tensor and autograd operations.
A VS Code extension to view and compare Weights & Biases training runs directly in the editor with interactive charts and AI context export.
A VS Code extension for viewing large datasets (JSONL/Parquet/CSV) instantly without crashes, with 16 production LLM tokenizers for accurate token counting.
A JavaScript neural network example that learns to predict angles between two points using synaptic.js.
A JavaScript neural network example that learns to predict whether a beer glass is half full or half empty based on user decisions.
A dependency-free statistics, linear algebra, and machine learning library for the V programming language, focused on product analytics.
A Ruby gem for building generative machine learning models from time series data.
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