privacy and security considerations in machine learning
Privacy and security considerations in machine learning refer to the measures and precautions taken to protect the confidentiality, integrity, and availability of data during the development, deployment, and usage of machine learning models.
Requires login.
Related Concepts (1)
Similar Concepts
- cybersecurity and data privacy
- data collection and usage practices in machine learning
- data privacy and security
- ensuring diversity and inclusivity in machine learning algorithms
- privacy and data ethics in ai systems
- privacy and data protection
- privacy and data protection in ai
- privacy and data usage in ai
- privacy and security concerns
- privacy and security in blockchain
- privacy concerns in ai
- privacy concerns in ai governance
- privacy concerns in recommender systems
- privacy concerns in robotics
- privacy concerns in the age of ai