berkeleybop/artificial-intelligence-ontology
An ontology modeling classes and relationships describing deep learning networks, their component layers and activation functions, machine learning methods, as well as AI/ML potential biases.
This provides a structured way to define and categorize components of artificial intelligence and machine learning systems. It takes in descriptions of deep learning networks, layers, activation functions, and methods, and outputs a standardized, machine-readable vocabulary for these concepts, including potential biases. Researchers, data scientists, and ethicists working with AI systems would use this to ensure consistent terminology and understanding.
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Use this if you need a common, explicit framework to describe and reason about the structure, function, and potential biases within AI and machine learning models.
Not ideal if you are looking for a software library to build or train AI models, as this is a definitional tool, not a development one.
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45
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9
Language
Jupyter Notebook
License
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Last pushed
Nov 12, 2024
Commits (30d)
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