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Machine Learning and Deep Learning for the PHP language.
Home Page:https://rubixml.com
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A high-level machine learning and deep learning library for the PHP language.
A library and extension that provides objects for scientific computing in PHP.
An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
A standalone inference server for trained Rubix ML estimators.
Use the famous CIFAR-10 dataset to train a multi-layer neural network to recognize images of cats, dogs, and other things.
An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.
Handwritten digit recognizer using a feed-forward neural network and the MNIST dataset of 70,000 human-labeled handwritten digits.
The original lightweight introduction to machine learning in Rubix ML using the famous Iris dataset and the K Nearest Neighbors classifier.
An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.
Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.
Demonstrating unsupervised clustering using the K Means algorithm and synthetic color data.
Build a classifier to predict the outcome of Dota 2 games with the Naive Bayes algorithm and results from 102,944 sample games.
Use the K Nearest Neighbors algorithm to predict the probability of a divorce with high accuracy.
Experimental features for the Rubix ML library.
Detect unhappy customers with Naive Bayes and 19 categorical features.
An example project demonstrating the use of machine learning to identify microbe taxonomies from their DNA sequences.
Client-side SDK for Rubix ML Server to use in your PHP applications.
A deep learning library for PHP powered by TensorFlow.
Digital signatures made by humans.
