Spam classification application written in PHP and the Rubix ML library. The Random Forest classifier was used for classification.

A standalone inference server for trained Rubix ML estimators.

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

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

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

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

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

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

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

Experimental features for the Rubix ML library.

Train your Miner with previously entered data. Start collecting data from them automatically. Supports semi-structured data-sctructures (such as PDF invoices) and unstuctured data (free text like emails)

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

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

Latent Semantic Analysis For Question Classification With K-Nearest Neighbor (2020-2021)

Machine Learning library for PHP

Film review sentiment analysis using php-ml

SentimentAnalysis using PHP RubixML library!