RubixML/ML

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PHP
License
MIT License
Created over 6 years ago
Updated about 1 month ago

RubixML/ML

RubixML

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

Rubix ML

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

Tensor extension for fast Matrix/Vector computing

Optional

GD extension for image support
Mbstring extension for fast multibyte string manipulation
SVM extension for Support Vector Machine engine (libsvm)
PDO extension for relational database support
GraphViz for graph visualization

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

Join Our Telegram Channel

Contributing

See CONTRIBUTING.md for guidelines.

License

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

Tensor

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

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

A standalone inference server for trained Rubix ML estimators.

CIFAR-10

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

Housing

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

MNIST

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

Iris

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

Credit

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

HAR

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

Colors

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

Dota2

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

Divorce

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

Extras

Experimental features for the Rubix ML library.

Churn

Detect unhappy customers with Naive Bayes and 19 categorical features.

DNA

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

DL

A deep learning library for PHP powered by TensorFlow.

Client

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

Signatures

Digital signatures made by humans.