Machine Learning for AEC

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Practical ML for AEC: from data to design

Authorgerald-ica
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Machine learning-driven workflows that translate complex AEC data into actionable insights, enabling faster, data-informed design, evaluation, and monitoring.

Core Features & Use Cases

  • ML methodologies for AEC: vision, prediction, and generative models tailored to architectural design, energy simulation, and site analysis.
  • Pipeline-oriented guidance: practical pipelines for data preparation, model selection, evaluation, and deployment in architectural workflows.
  • Real-world applications: floor plan understanding, energy/daylight prediction, and generative design exploration from adjacency graphs to 3D massing.

Quick Start

Create a simple floor-plan with two bedrooms and a living area within a 60m2 footprint.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: Machine Learning for AEC
Download link: https://github.com/gerald-ica/opencode-config-snapshot/archive/main.zip#machine-learning-for-aec

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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