Open Source Python Scientific/Engineering Software for ChromeOS

PyTensor is a fork of Aesara, a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007. A hackable, pure-Python codebase. Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that currently provides compilation via C, JAX, and Numba. Based on one of the most widely-used Python tensor libraries: Theano.

Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning.

The Player Project: Player is a networked interface to robots and sensors. Stage and Gazebo are Player-friendly multiple-robot simulators. The software aims for POSIX compliance and runs on most UNIX-like OS's. Some parts also work on Windows.

MSTParser is a non-projective dependency parser that searches for maximum spanning trees over directed graphs. Models of dependency structure are based on large-margin discriminative training methods. Projective parsing is also supported. mstparser 0.5.1 is now available via Maven Central. If you use Maven as your build tool, then you can add it as a dependency in your pom.xml file: <dependency> <groupId>net.sourceforge.mstparser</groupId> <artifactId>mstparser</artifactId> <version>0.5.1</version> </dependency>

Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.

This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed to address problems in epidemiological data mining to identify complex patterns relating predictive attributes in noisy datasets to disease phenotypes of interest. ExSTraCS combines a number of recent advancements into a single algorithmic platform. It can flexibly handle (1) discrete or continuous attributes, (2) missing data, (3) balanced or imbalanced datasets, and (4) binary or many classes. A complete users guide for ExSTraCS is included. Coded in Python 2.7.

A Python interface to the Wordnet database of word meanings and lexical relationships. allows the user to type expressions such as N['dog'], hyponyms(N['dog'][0]), and closure(ADJ['red'], SYNONYM) to query the database for lexical relationships.

Spirit, a different way to write! You guide your mouse through streams of predicted words. As the intelligent agent learns your writing style, its predictions become more accurate. You can prime Spirit with the prose and poetry of any author!

The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.

This project has moved to GitHub.

A.I. security app. Development ceased.

The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.

Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.

This project develops a simple, fast and easy to use Python graph library using NumPy, Scipy and PySparse.

A three-step approach towards experimental brain-computer-interfaces, based on the OCZ nia device for EEG-data acquisition and artificial neural networks for signal-interpretation.

Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization.

Chloe - a chatterbot with charisma. Learns from experience, and speaks any language you teach her. Perhaps even useful, but surely entertaining.

DrPangloss is a python implementation of a three operator genetic algorithm, complete with a java swing GUI for running the GA and visualising performance, generation by generation

Ellogon is a multi-lingual, cross-platform, general-purpose language engineering environment.

We experiment with Evolution of Artifical Neural Networks, combining the two fields of Evolutionary Computation and ANNs. Our methods are applied to a variety of interesting problems. To learn more, click on "Home Page", "Mail", or "Files".

Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The

HORUS is a system for knowledge acquisition, hypothesis generation, inference and learning. It is an interactive, internet environment accessible to a diverse community of users (public-access or membership basis) - see also UMKAILASH project for more.

The Hydroponic Automation Platform Initiative (HAPI) develops and provides hardware and software components for automating food production using hydroponic, aquaponics, and precision agriculture techniques. High-yield production in urban settings is one of the primary goals. Artifacts include hardware design (mainly Arduino-based), firmware, management software and reporting modules.

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.

Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.