TypeScript & JavaScript machine learning library
various machine learning routines for node
An open-source machine learning framework.
AWS SDK for JavaScript Machine Learning Client for Node.js, Browser and React Native
Web Assembly streaming Opus decoder with Machine Learning enhancements
Machine learning category of aws-amplify
Machine learning algorithms.
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
Automatic machine learning for kubernetes
A friendly machine learning library for the web.
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
machine learning for data cloud
Simple machine learning module for node.js & browsers.
A library to recursively retrieve and serialize Notion pages with customization for machine learning applications.
Machine learning tools
GPU Javascript Library for Machine Learning
Make music with machine learning, in the browser.
A nodejs module for local and remote Inter Process Communication (IPC), Neural Networking, and able to facilitate machine learning.
A nodejs module for local and remote Inter Process Communication (IPC), Neural Networking, and able to facilitate machine learning.
Automatic machine learning for kubernetes
machine-learning
Machine Learning library for the web and Node
Machine learning supporting utilities
Webpack plugins for the Machine Learning-driven bundler
A Rust library for machine learning algorithms
Rust wrappers for the PyTorch AOTInductor api.
GPU Computing Library
A neural network library in Rust.
A neural network library in Rust.
A data loader
Command-line interface for the Axonml ML framework
ONNX import/export support for the Axonml ML framework
Model serialization for Axonml ML framework
High-level training, benchmarking, and adversarial training infrastructure for AxonML
Terminal User Interface for Axonml ML Framework
Reinforcement learning for Rust. Backend-agnostic over modern Rust ML frameworks.
This workbench holds a collection of machine learning methods in Ruby. Rather than specializing on a single task or method, this gem aims at providing an encompassing framework for any machine learning application.
A machine learning gem
Microsoft Azure Machine Learning Management Client Library for Ruby
Gem to build simple regressors and classifiers into your application, without necessarily having to understand all the math behind.
Microsoft Azure Machine Learning Services Management Client Library for Ruby
Official AWS Ruby gem for Amazon Machine Learning. This gem is part of the AWS SDK for Ruby.
Vertex AI enables data scientists, developers, and AI newcomers to create custom machine learning models specific to their business needs by leveraging Google's state-of-the-art transfer learning and innovative AI research. Note that google-cloud-ai_platform-v1 is a version-specific client library. For most uses, we recommend installing the main client library google-cloud-ai_platform instead. See the readme for more details.
AutoML makes the power of machine learning available to you even if you have limited knowledge of machine learning. You can use AutoML to build on Google's machine learning capabilities to create your own custom machine learning models that are tailored to your business needs, and then integrate those models into your applications and web sites. Note that google-cloud-automl-v1 is a version-specific client library. For most uses, we recommend installing the main client library google-cloud-automl instead. See the readme for more details.
AutoML makes the power of machine learning available to you even if you have limited knowledge of machine learning. You can use AutoML to build on Google's machine learning capabilities to create your own custom machine learning models that are tailored to your business needs, and then integrate those models into your applications and web sites. Note that google-cloud-automl-v1beta1 is a version-specific client library. For most uses, we recommend installing the main client library google-cloud-automl instead. See the readme for more details.
High level plug-and-play interface for composing Machine Learning applications
This is a library for machine learning. You can use AdaBoost and Naive Bayes easily.
A simple hello world gem
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