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:
https://cs.stanford.edu/~jhoffman/domainadapt/ - domain adaptation projects / computer vision
http://www.deeplearningbook.org/ - contains lecture slides, tutorials and exercises
http://www.gaussianprocess.org/ - contains reading materials on GPs, code and datasets
2) The Future of Personalized Healthcare: https://rockhealth.com/reports/predictive-analytics/
Personalized Health with Gaussian Processes https://www.youtube.com/watch?v=si5e-ekZlnQ
- A discussion on Machine Learning (GPs, Deep Models) and Personalized Learning.