University of Hong Kong

This course examines algorithms, tools, practices, and applications of machine learning. Topics include core methods such as supervised learning (classification and regression), unsupervised learning (clustering, principal component analysis), Bayesian estimation, neural networks; common practices in data pre-processing, hyper-parameter tuning, and model evaluation; tools/libraries/APIs such as scikit-learn, Theano/Keras, and multi/many-core CPU/GPU programming.

It aims at enhancing students’ communicative competence, i.e. listening, speaking, reading and writing. Students will be exposed to Chinese society and culture through a variety of topical discussions and different audiovisual media including films (movies) and Vlog.   

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This course is an introduction to philosophical issues about mind and knowledge. These include metaphysical questions about what minds are, such as whether the mind is something non-physical or whether it is some kind of computer, and questions about what knowledge is and how we can obtain it. The course examines epistemological questions about the limitations of human knowledge, such as whether we can really know what other people's experiences are like or whether God exists. Assessment: 100% coursework.

This course examines lasers and laser spectroscopy techniques. It covers fundamentals of optical processes and spectroscopic techniques; lasers as spectroscopic light sources; components of spectroscopic instruments; raman spectroscopy; nonlinear spectroscopy; nonlinear optics; time-resolved spectroscopy; photoelectron spectroscopy; and new developments in laser spectroscopy.

This course examines the food experiences and practices and their ideological effects that shape diners and their city. It also traces the crystallization of a conscious distinction of Hong Kong food and their influences among the residents of the city and overseas.