MA4550 - A Mathematical Introduction to Machine Learning for Data Sciences | ||||||||||
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* The offering term is subject to change without prior notice | ||||||||||
Course Aims | ||||||||||
Machine learning is the science of getting computers to learn the hidden patterns from the massive size of data and it is the most important methodology run on computers for artificial intelligence. The theoretic core of the machine learning consists of three elements: the mathematics to characterize the hidden structures and relations of the data, the statistical learning theories to build the correct models and assessment tools, and lastly, the computational algorithms to practically solve the final numerical problems.
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Assessment (Indicative only, please check the detailed course information) | ||||||||||
Continuous Assessment: 50% | ||||||||||
Examination: 50% | ||||||||||
Examination Duration: 2 hours | ||||||||||
For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained. | ||||||||||
Detailed Course Information | ||||||||||
MA4550.pdf |