David Stasiuk and I instructed a 4-hour workshop on Machine Learning as part of AEC Tech 2018 - an annual conference hosted by Thornton Tomasetti. The workshop focused on demonstrating architectural use cases for machine learning in the context of our open source LunchBoxML tools. Our course examples are now available on the LunchBoxML Bitbucket … Continue reading AEC Tech 2018 – LunchBoxML Workshop Examples
Like with past summers, I thought I'd share some of the things our summer researchers are investigating. In 2016, the team created computational prototypes focused on real-world workflows ranging from building analysis to geometric interoperability. In 2017, the focus was on data analysis and resulted in building data visualization workflows and the first version of … Continue reading Summer 2018 – Part 1
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
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
