algorithmic modeling for Rhino
The purpose of the Owl plug-in is to constitute a new data type named Tensor, thanks to which the Grasshopper users will be able to work with so-called "big-data". This will further open up new possibilities to use more sophisticated machine-learning tools, which require big data sets to be effective.
The core library of the Owl plug-in is open sourced, and provides the developers with methods to read/write and use the Tensor data within the GH (and outside of it).
Additionally the Owl.Accord.GH.gha plug-in is the first extension based on the Owl core, utilizing few of the machine-learning methods sourced from the Accord framework.
Download at: http://www.food4rhino.com/app/owl
Core libraries, open-sourced: https://github.com/mateuszzwierzycki/Owl
Some parts of the plug-in depend on the Accord framework: https://github.com/accord-net/framework
Latest Activity: Dec 22, 2017
Hi everyone & Mateusz - Owl is brilliant, and thanks for creating it.I wanted to represent the T-SNE data in grid form, so I've copy-pasted and hooked some things up implemented …Continue
Started by Dan Taeyoung. Last reply by Pablogomez Dec 22, 2017.
While Owl contains some small-scale methods for machine learning, you might want to use more recent deep-learning methods like the ones available in TensorFlow.The solution is:Get the data from…Continue
Started by Mateusz Zwierzycki. Last reply by Mateusz Zwierzycki Apr 15, 2017.