Search Results for "learn language"

...Because the repository captures a historical commit log with explanations of changes, readers can trace decisions and learn how different configuration elements interact.

Neorg is an all-encompassing tool based around structured note taking, project and task management, time tracking, slideshows, writing typeset documents and much more. The premise is that all of these features are built on top of a single base file format (.norg), which the user only has to learn once to gain access to all of Neorg's functionality. Not only does this yield a low barrier for entry for new users it also ensures that all features are integrated with each other and speak the same underlying language. The file format is built to be expressive and easy to parse, which also makes .norg files easily usable anywhere outside of Neorg itself. ...

Agena is an easy-to-learn procedural programming language designed for science, scripting, and many other applications. Binaries are available for Windows, Linux, Solaris, OS/2, Mac OS X, Raspberry Pi and DOS.

Vanda Engine is a free and open source 3D game engine for Windows. I'm developing this game engine for years to help the students and other enthusiast learn game engine programming and develop 3D games for free. While giant companies are building game engines with huge budget and a lot of manpower, I'm developing this free 3D game engine alone with no budget. I have published step by step tutorials about Vanda Engine, 3D tools, and COLLADA format: https://vanda3d.org/tutorials/ Please...

char-rnn is a classic codebase for training multi-layer recurrent neural networks on raw text to build character-level language models that learn to predict the next character in a sequence. It supports common recurrent architectures including vanilla RNNs as well as LSTM and GRU variants, letting users compare behavior and output quality across model types. It is straightforward: you provide a single text file, train the model to minimize next-character prediction loss, then sample from the trained network to generate new text one character at a time in the style of the dataset. ...