Privacy and Security

Machine learning solutions can involve the processing of sensitive personal information, raising concerns about data privacy and security. To protect the privacy of individuals, it's important to follow data protection regulations, anonymize data where possible, and implement robust security measures. Techniques like differential privacy and federated learning can help protect sensitive data while still enabling the development of effective machine learning models.