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Machine learning is a subset of artificial intelligence that enables systems to learn from data and improve over time without explicit programming. The principles include supervised and unsupervised learning, algorithm development, and performance evaluation.
Organizations and individuals who develop or deploy machine learning models are typically required to file machine learning and principles documentation, especially if it affects compliance, ethics, or regulations.
To fill out machine learning and principles, you need to provide detailed information on the models used, the training data, the outcomes, and the ethical considerations. This often involves specific forms or templates provided by regulatory authorities.
The purpose is to ensure transparency, accountability, and ethical usage of machine learning systems. It helps organizations demonstrate compliance with regulations and fosters trust among users and stakeholders.
Reported information typically includes model descriptions, data sources, accuracy metrics, risk assessments, and methodologies for handling biases or ethical concerns.
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