Machine Learning and Privacy

This lecture covers the fundamental concepts of machine learning and privacy, including the training process, privacy concerns, privacy attacks, and the implications of collaborative machine learning. It delves into topics such as membership inference attacks, model inversion, and gradient inversion, highlighting the privacy risks associated with trained machine learning models. The instructor emphasizes the importance of understanding the privacy implications of machine learning models and the potential risks of data leakage and privacy attacks.