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Stellarium is a free GPL software which renders realistic skies in real time with OpenGL. It is available for Linux/Unix, Windows and macOS. With Stellarium, you really see what you can see with your eyes, binoculars or a small telescope. Stellarium is a free open source planetarium for your computer. It shows a realistic sky in 3D, just like what you see with the naked eye, binoculars or a telescope. Plugin system adding artifical satellites, ocular simulation, telescope control and more. ...

This code works best with the NodeMCU V2 ESP8266 module and an 0.96" OLED display. To get you up and running in no time we created a kit that contains all the necessary parts. By buying this and other kits from us you are funding the maintenance and development of this library. Make sure you use a version of the Arduino IDE which is supported by the ESP8266 platform. If you are using the PlatformIO environment for building, choose one of the available IDE integration or the Atom-based IDE, install libraries 561, 562, and 563 with "platformio lib install", adapt the WeatherStationDemo.ino file to your needs. ...

DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network.

...Today, this is a pitiable sight, because modern computer systems are coupled by networks and support multi threading. We create a distributed system with Apache thrift and the C-API of glpk. Now, it is possible to use as many cores in a network as you want. With a focus on the MILP methods we implement a load balancing and speed up the solving process in a multiplicative way. Sometimes we have super-linear speedup with a small set of hardware. With a splitting of problems, parallel computing and distributing the actual best solution to all running processes we solve CBP much faster than a sequential processing can do.

this is where you will find all of my completely free software. both free as in "free speech" and free as in "free beer"! this project space has been established so we can all help eachother with software development. in other words, we're here for the learning experience. i will always give my source code so that you may study it and practice it yourself and/or provide constructive feedback so you can help me learn how I can make improvements.

Flatland is the virtual environment developed to perform these investigations. Using Flatland as the base environment scientists can visualize and explore both their data and the computations that manipulate that data. Imagine, if you will, a scientist able to examine the real-time results of a simulation and, when he notices an anomally he would like to investigate, he turns to the program running the simulation and examines the code, possibly changing it on the fly. This is the dream of Flatland.

...Commercial licensing (use incompatible with GPLv3) will be available via an elected or appointed non-profit Facilitator. Revenue will be invested per the discretion of the Facilitator and an advisory board. By contributing to this project, you agree to these terms. [See our Wiki for more information](https://sourceforge.net/p/openshader/wiki/)

...It is a more learning-oriented project than something intended to provide a wide set of features. The approach to the OpenGL in this engine is something very experimental born from my own thoughts and can be usefull in future. If you want to help for your portfolio just ask: the TODO list is very long :)

...I wrote it over three years ago, and wrote it in quite a hurry when I did. If you compare this stuff with my GPE code, its like night and day. Well, hopefully somebody learning to work with OGRE or to program in C++, might find it useful

DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machine learning algorithms. It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure. It can handle highly non-linear dependencies between multivariate random variables. The particle based inference can answer arbitrary questions given the provided evidence and can even cope with multimodal densities. The library supports the most common types of densities and conditional densities, like uniform or normal densities and facilitates user defined density functions. ...