Description
Many industries have embraced machine learning, but its uses are still widely misunderstood. This class will demystify machine learning by providing a case study on how KLH Engineers used Python to create a machine-learning model to bridge the gap between AutoCAD software and Revit software in the architecture, engineering, and construction industry. This study will illustrate which concrete problems machine learning can solve, such as converting thousands of possible AutoCAD layer names into useable Revit elements by utilizing conversions already made by hand. Attendees will discover how to use their own historical data to enhance their company’s process workflow.
Key Learnings
- Discover how machine learning can be used as a tool in the AEC industry
- Discern what problems can be solved using machine learning
- Learn how to integrate a concrete use of machine learning into a company’s workflow
- Learn how to enhance a company’s process workflow by using historical data