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.
Ruby language bindings for the LIBSVM library, enabling support vector machine (SVM) classification and regression in Ruby.
A comprehensive scientific computing and AI/ML library in pure Rust, offering SciPy-compatible APIs with 10-100x performance gains.
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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