New Machine Learning Examples with LunchBoxML

Posted on by Nate

Last year, we introduced LunchBoxML - a machine learning (ML) plugin for Grasshopper and Dynamo that uses the Accord framework. LunchBoxML introduces several generalized supervised and unsupervised learning tools to visual programming including regression analysis, neural networks, and mixture models. We have published a few new examples to the Bitbucket repository to demonstrate the application … Continue reading New Machine Learning Examples with LunchBoxML

LunchBoxML for Dynamo

Posted on by Nate

This past summer, we released LunchBoxML for Grasshopper. Many have asked if we would publish a version for Dynamo. Ask no more! As of the last update, we have included the first version of LunchBoxML for Dynamo! By having this capability in Dynamo, users are able to start leveraging data from Revit to feed the … Continue reading LunchBoxML for Dynamo

Machine Learning with LunchBoxML

Posted on by Nate

Earlier this summer, I previewed some of our research on machine learning which focused on potential applications for the building industry. I am now pleased to announce that these explorations have been released as a new extension to our LunchBox tools for Grasshopper: LunchBoxML. LunchBoxML exposes new open source components built on a popular machine … Continue reading Machine Learning with LunchBoxML

Analytics, machines, and our summer so far…

Posted on by Nate

We are in the heat of the summer season and we have invited summer interns to work with us to experiment with new concepts and technologies. In 2016, we focused on rapid development of focused problem-first workflows and published our content as an open source project. This year, Ally and Nazanin have joined us for … Continue reading Analytics, machines, and our summer so far…