What is Machine Learning?
Machine learning is a method where computers learn from data instead of being explicitly programmed. Rather than writing rules like “if area > 100 and perimeter < 50, then classify as Type A”, you provide examples and the algorithm discovers the patterns on its own. Think of it like this: instead of telling the computer how to classify rooms, you show it hundreds of already-classified rooms and it learns what makes each type different.Why Machine Learning in Dynamo?
As AEC professionals, we work with enormous amounts of geometric and spatial data every day — building elements, room layouts, structural components, urban plans. Machine learning helps us:- Find patterns we cannot see manually in large datasets
- Automate repetitive classification tasks that would take hours by hand
- Predict properties of new elements based on learned relationships
- Detect anomalies and quality issues in building models automatically
You do not need any programming or data science background to use this package. Every algorithm is wrapped in a simple Dynamo node — just connect your data and get results.
Package Overview
Which Model Should I Use?
| I want to… | Use this | Example |
|---|---|---|
| Classify elements into categories | Classifier | Room type, material type, zone category |
| Find natural groups in data | Clustering | Building typologies, spatial zones |
| Detect unusual/outlier elements | Density | Modeling errors, abnormal dimensions |
| Predict a numerical value | Regression | Area, cost, energy consumption |