This project is dedicated to create an automated response as an architect to a given construction site. It leverages neural networks to educate the model on how to design a museum, building, or any other architectural structure for a specific location. The project utilizes programming languages such as Python and a training set comprised of many Revit models.
This project is a research project in my university.

Neural Network Training: The core functionality of this project involves training a neural network to understand and generate architectural responses based on the given context and site parameters.

Educational Model: The model is trained on my responses throughout my own educational journey, ensuring a personalized and unique approach to architectural design.

Python Implementation: The project is implemented primarily in Python, making use of popular libraries for neural network training and natural language processing.

Clone the repository: git clone https://github.com/EzgiTastan/actAsAnArchitect.git

Navigate to the project directory: cd actAsAnArchitect

Install the required dependencies: pip install -r requirements.txt

Data Preparation: Ensure that your training data is organized in a structured format. The training set should consist of architectural responses provided by the architect to different construction site scenarios.

Training the Model: Run the training script to train the neural network: python train.py Adjust hyperparameters and configurations as needed in the script.

Generating Architectural Responses: Once the model is trained, use the generation script to get responses for specific construction sites: python generate_response.py --site_parameters "path/to/site_parameters.json" Replace "path/to/site_parameters.json" with the actual path to the file containing construction site parameters.

Contributions are welcome! If you have ideas for improvements, bug fixes, or additional features, please open an issue or submit a pull request.

This project is licensed under the MIT License.

For questions or discussions, feel free to reach out to me: kedigunesi [at] gmail.com

To optimize performance and enhancing usability, these items will be added over time:

Graphical User Interface (GUI) Parameter Tuning Interface Model Evaluation Metrics Error Handling Logging and Debugging Deployment Scripts CI/CD pipelines