The "ML-Graphology" repository is dedicated to the exploration of machine learning techniques applied to graphology, the analysis of handwriting. This repository contains code, datasets, and resources for developing machine learning models to infer personality traits, emotions, or other characteristics from handwriting samples.
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Clone the repository:
https://github.com/Narla-Venkata-Anand-Sai-Kumar/ML-Graphology.git
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Navigate to the project directory:
cd ML-Graphology -
Explore the code and datasets available to understand how machine learning algorithms can be applied to graphology.
- Dataset: Includes datasets of handwriting samples for training and testing machine learning models.
- Models: Contains implementations of machine learning models for graphological analysis.
- Visualization: Provides tools for visualizing handwriting samples and model predictions.
Contributions to ML-Graphology are welcome! If you have ideas for improving the machine learning models, adding new features, or enhancing the dataset, feel free to fork the repository and submit a pull request.
This project is licensed under the [specify your license type here, e.g., MIT License].
For any questions or feedback regarding ML-Graphology, please reach out to [email protected].