mateuszzwierzycki/Owl

This system is a machine learning and data processing framework, primarily designed as a plugin for the Grasshopper visual programming environment. It provides components for constructing, training, and visualizing neural networks, as well as implementing reinforcement learning algorithms like Q-Learning. The codebase also supports image processing, clustering, and MQTT-based data exchange, all built upon the Accord.NET library.

This period focused on integrating the Owl machine learning library with the Grasshopper environment, introducing new data types and component structures for seamless workflow integration. Simultaneously, the codebase underwent significant structural changes, including the creation of the Owl.ParamSetup project and the reorganization of the Owl.Learning module. These efforts were supported by updated dependencies and the addition of core repository infrastructure.

9 changes

This period focused on expanding the library's machine learning capabilities, introducing a complete Q-Learning implementation and a new neural network architecture with backpropagation support. The work also extended the Grasshopper interface to include supervised, unsupervised, and reinforcement learning components, alongside new utilities for video processing and MQTT connectivity.

7 changes

mateuszzwierzycki/Owl was measured the same way every project in this corpus was: the same rubric, at a pinned commit, with the result published in full. Point the surveyor at a repository you know and see whether you agree with it.