FB8918 - Machine Learning for Business Research | ||||||||||
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| * The offering term is subject to change without prior notice | ||||||||||
Course Aims | ||||||||||
Machine learning stands the core for many business
models nowadays. This course aims to teach doctoral students in College of
Business machine learning models and tools and enable them to conduct related business
research. The course will cover supervised learning in depth, including regression,
classification, regularization, tree-based methods, ensemble methods etc., and
will also introduce the basic concepts and tools of unsupervised learning,
including clustering and principle component analysis, etc. This course focuses
on practical training using business data, including marketing and financial
market data, as well as unstructured text data in news media. | ||||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||||
Continuous Assessment: 100% | ||||||||||
Detailed Course Information | ||||||||||
| FB8918.pdf | ||||||||||
Useful Links | ||||||||||
| College of Business | ||||||||||
