This week, I will be leading a workshop as part of Data Day 2019 in Seattle. The workshop will focus on uses of machine learning in architecture and construction with hands-on examples of LunchBoxML for Grasshopper. If you are attending the workshop or just want some of the materials for your own reference, here they … Continue reading LunchBoxML @ Data Day 2019
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
PROVING GROUND 