Machine Learning
Showing 36 of 1845 projects
A reinforcement learning toolbox implementing TRPO and A3C algorithms for continuous action spaces.
An open-source machine learning library for regression tasks using the Relevance Vector Machine (RVM) technique.
A simple machine learning library for Crystal with a working Bayes classifier and upcoming decision tree.
A Scala machine learning library with simple, readable implementations of classic algorithms for prototyping and education.
Native Julia implementations of standard SVM algorithms, including Pegasos and Dual Coordinate Descent.
A GitHub Action that submits Argo Workflows from GitHub Actions to enable CI/CD for machine learning on Kubernetes.
An open-source machine learning solution for the Santander Value Prediction Challenge on Kaggle.
A scalable Python tool for multicalibration that ensures ML model predictions are well-calibrated across all data segments, not just globally.
A graphical computation package for Torch that enables graph-based operations and visualization.
A Julia package implementing Latent Dirichlet Allocation (LDA) topic models with collapsed Gibbs sampling inference.
A Python implementation of the Optimum-Path Forest classifier for machine learning tasks.
A phonetic algorithm for indexing Chinese characters by sound, estimating distance between words and finding similar-sounding candidates.
A collection of classical machine learning models implemented with TensorFlow 2 and Keras, featuring TensorBoard visualizations.
A Redis-backed naive Bayesian classification system for Ruby applications.
Ruby bindings for Annoy (Approximate Nearest Neighbors Oh Yeah), enabling fast nearest neighbor searches in Ruby applications.
A native Objective-C framework for experimenting with neural networks and natural language processing on macOS and iOS.
A collection of resources and examples for learning fundamental machine learning techniques and algorithms.
A Python library for building and training feedforward neural networks with GPU support and mini-batch learning.
AI-powered code completion extension for JupyterLab that suggests completions based on machine learning models trained on billions of lines of open-source code.
An R package implementing Restricted Boltzmann Machines for collaborative filtering and feature learning.
OCaml bindings for Python's scikit-learn machine learning library.
An incomplete collection of academic and research presentation slides by Scott Wen-tau Yih.
A collection of easy-to-use machine learning datasets for Torch7 with built-in preprocessing and sampling utilities.
A Rust library for implementing Self-Organizing Maps (SOM) with customizable training and serialization.
A curated list of awesome Keras projects, libraries, and resources for deep learning.
A legacy Ruby SDK for accessing AlchemyAPI's text analysis and image recognition AI services.
A Docker-based starter kit providing pre-configured Jupyter notebook environments for machine learning with TensorFlow, PyTorch, and essential libraries.
Detects when you're physically holding your phone using device sensors and machine learning.
A convolutional neural network solution for the GalaxyZoo galaxy classification challenge, achieving 9th place with a score of 0.08246.
An implementation of artificial neural networks in Ruby for experimentation and learning about ANN fundamentals.
A GitHub Action for compiling and deploying Kubeflow Pipelines to a Kubeflow cluster on Google Cloud Platform.
A lightweight logging library for machine learning research experiments.
Provides Lua/Torch bindings for the Randomkit library, enabling random number generation from various statistical distributions.
Benchmarks comparing machine learning inference performance for tabular models in Go, focusing on low-latency single-sample predictions.
A Go library implementing Genetic Algorithm and Particle Swarm Optimization for solving optimization problems.
A Ruby client library for interacting with the Milvus vector database API.
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