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Rubix ML

PHP from Packagist Latest Stable Version Downloads from Packagist Code Checks GitHub

A high-level machine learning and deep learning library for the PHP language.

  • Developer-friendly API is delightful to use
  • 40+ supervised and unsupervised learning algorithms
  • Support for ETL, preprocessing, and cross-validation
  • Open source and free to use commercially

Installation

Install Rubix ML into your project using Composer:

$ composer require rubix/ml

Requirements

  • PHP 7.4 or above

Recommended

Optional

Documentation

Read the latest docs here.

What is Rubix ML?

Rubix ML is a free open-source machine learning (ML) library that allows you to build programs that learn from your data using the PHP language. We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects.

Getting Started

If you are new to machine learning, we recommend taking a look at the What is Machine Learning? section to get started. If you are already familiar with basic ML concepts, you can browse the basic introduction for a brief look at a typical Rubix ML project. From there, you can browse the official tutorials below which range from beginner to advanced skill level.

Tutorials & Example Projects

Check out these example projects using the Rubix ML library. Many come with instructions and a pre-cleaned dataset.

Interact With The Community

Contributing

See CONTRIBUTING.md for guidelines.

License

The code is licensed MIT and the documentation is licensed CC BY-NC 4.0.

Rubix's Projects

churn icon churn

Detect unhappy customers with Naive Bayes and 19 categorical features.

cifar-10 icon cifar-10

Use the famous CIFAR-10 dataset to train a multi-layer neural network to recognize images of cats, dogs, and other things.

client icon client

Client-side SDK for Rubix ML Server to use in your PHP applications.

colors icon colors

Demonstrating unsupervised clustering using the K Means algorithm and synthetic color data.

credit icon credit

An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.

divorce icon divorce

Use the K Nearest Neighbors algorithm to predict the probability of a divorce with high accuracy.

dl icon dl

A deep learning library for PHP powered by TensorFlow.

dna icon dna

An example project demonstrating the use of machine learning to identify microbe taxonomies from their DNA sequences.

dota2 icon dota2

Build a classifier to predict the outcome of Dota 2 games with the Naive Bayes algorithm and results from 102,944 sample games.

extras icon extras

Experimental features for the Rubix ML library.

har icon har

Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.

housing icon housing

An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.

iris icon iris

The original lightweight introduction to machine learning in Rubix ML using the famous Iris dataset and the K Nearest Neighbors classifier.

ml icon ml

A high-level machine learning and deep learning library for the PHP language.

mnist icon mnist

Handwritten digit recognizer using a feed-forward neural network and the MNIST dataset of 70,000 human-labeled handwritten digits.

sentiment icon sentiment

An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.

server icon server

A standalone inference server for trained Rubix ML estimators.

tensor icon tensor

A library and extension that provides objects for scientific computing in PHP.

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