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.

Film review sentiment analysis using php-ml

SentimentAnalysis using PHP RubixML library!

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

Machine Learning library for PHP

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

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)