Open Source Python Artificial Intelligence Software

Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read introduction article and a reference manual accompanies the library with examples and recommendations on how to use the library. Several graphical user interfaces are also available for the library.

Magic is an open source all-in-one AI productivity platform designed to help organizations build, deploy, and scale AI-driven applications efficiently. It is not a single tool but a complete product ecosystem composed of multiple integrated systems that work together to enhance productivity across different business scenarios. Magic centers around a general-purpose AI agent system called Super Magic, which can autonomously understand tasks, plan actions, execute workflows, and perform error correction. Alongside this, Magic includes a visual workflow engine that enables users to design complex AI processes using a drag-and-drop interface without requiring extensive coding knowledge. It also provides an enterprise-grade instant messaging system that integrates AI conversations with internal communication, allowing teams to collaborate while leveraging intelligent assistants. Its architecture is built using a microservices approach with containerized services.

This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.

A.I. security app. Development ceased.

Brainiac, Is C/C++ Libraries, Programs, And Python, And Lua Scripts For Neural Networking And Genetic Programming, In An Attempt To Create A "Glue-It-All-Together" Project, Striving Towards General Artificial Intelligence

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.

LinkMesh is an AI-driven WordPress plugin designed to streamline internal linking strategies. The tool helps users identify and fix orphan pages while providing semantic link suggestions that can be approved with a single click. By automating the discovery of relevant internal connections, LinkMesh assists in improving site structure and search engine visibility. Unlike traditional auto-linking tools, LinkMesh analyzes your existing content to identify relevant internal linking opportunities and build a stronger internal link structure for SEO. AI identifies semantically relevant connections, while the site owner remains in control of the final link placement. LinkMesh goes beyond simple keyword-based auto-linking by combining semantic SEO, keyword intelligence, internal PageRank analysis, and site-wide internal link management in one WordPress workflow. Documentation: https://linkmesh.co/documentation.html https://wordpress.org/plugins/ailinkmaster-internal-auto-manager/

Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.

The Genetic Architecture Framework is intended to explore and experiment with artificial life techniques using a genetic base for the physical and neural networks for the brain, in a game based simulated world.

Voice Conference Manager uses VoiceXML and CCXML to control speech recognition, text to speech, and voice biometrics for a telephone conference service. Say the names or numbers of people and VCM places them into the call. Can be hosted on public servers

Frontend and Backend Code for ArtikelSchreiber.com and UNAIQUE.NET Text Generator deutsch - Dein KI Text Generator kostenlos mit Künstlicher Intelligenz The Software as a Service can be found here: SEO Optimizer: Ghost Writer - Hausarbeiten schreiben mit KI and KI Text Generator This product includes software developed by Sebastian Enger, M.Sc. Copyright (c) 2023, Sebastian Enger, M.Sc. All rights reserved. Frontend and Backend Source Code for Project: https://github.com/sebastianenger1981/ https://www.artikelschreiber.com/ https://www.artikelschreiben.com/ https://www.unaique.net/ https://www.artikelschreiber.com/opensource/ https://www.unaique.com/

ch0 c-h-zero the chess engine!!! How well is it possible for your processor(s) to play chess? How well is it possible for someone AND your processor(s) to play chess? Would they let it fly, or manage it actively? --> Let's evolve !!!

This is implementation of CommitBERT: Commit Message Generation Using Pre-Trained Programming Language Model. CommitBERT is accepted in ACL workshop : NLP4Prog. Have you ever hesitated to write a commit message? Now get a commit message from Artificial Intelligence! CodeBERT: A Pre-Trained Model for Programming and Natural Languages introduces a pre-trained model in a combination of Program Language and Natural Language(PL-NL). It also introduces the problem of converting code into natural language (Code Documentation Generation). We can use CodeBERT to create a model that generates a commit message when code is added. However, most code changes are not made only by add of the code, and some parts of the code are deleted. We plan to slowly conquer languages that are not currently supported. To run this project, you need a flask-based inference server (GPU) and a client (commit module). If you don't have a GPU, don't worry, you can use it through Google Colab.

A collection of software made by Milos Rancic.

This software presents a flexible and configurable proposal for monitoring and management of real and virtual HPC infrastructures, compatible with paradigm of cloud computing. We help you to answer: 1) What is the performance of my resources? 2) What equipment and resources do we have already? 3) What do we need to upgrade or repair? 4) What can we consolidate to reduce complexity or reduce energy use? 5) What resources would be better reused somewhere else? Status: PreAlpha, so any help shall be welcome. Made for LINUX. GNU General Public License version 3.0 (GPLv3)