Personalized Machine Learning

MAS.S61 Spring 2017, Thursdays 1-3pm, room: E15-359


Materials to look into before the 1st class:

Books (general overview of machine learning):

(1) Bishop, Christopher M. "Pattern recognition." Machine Learning 128 (2006).

(2) Rasmussen, Carl Edward. "Gaussian processes for machine learning." (2006).

(3) Murphy, Kevin P. Machine learning: a probabilistic perspective. MIT press (2012).

Very useful resources: - domain adaptation projects / computer vision - contains lecture slides, tutorials and exercises - contains reading materials on GPs, code and datasets

News articles:

1) Personalized learning:

2) The Future of Personalized Healthcare:

Personalized Health with Gaussian Processes

- A discussion on Machine Learning (GPs, Deep Models) and Personalized Learning.