Faculteit | Gedrags- en MaatschappijWetenschappen |
Jaar | 2021/22 |
Vakcode | SOMINDW07 |
Vaknaam | Machine learning |
Niveau(s) | universitaire minor |
Voertaal | Engels |
Periode | semester I a |
ECTS | 2.5 |
Rooster | rooster.rug.nl |
Uitgebreide vaknaam | Fundamentals of Machine Learning: Theory and Practice | ||||||||
Leerdoelen | Students will be able to - understand the principles of machine learning and know the main approaches and their differences; - plan a machine learning experiment with appropriate settings; - approach existing ML Python resources with sufficient knowledge to pick and modify the needed libraries; - understand what data is necessary to run a machine learning experiment towards a given research question, and (pre)process it appropriately; - evaluate and analyse the results of a machine learning experiment; - describe scientifically the settings and the results of a machine learning experiment. |
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Omschrijving | This course will provide the theoretical and practical basis for running machine learning experiments in a variety of fields and tasks, where one requires data manipulation towards making predictions. The students will be exposed to both theory and tools, and will experiment with actual datasets. This will make them acquainted with the settings of machine learning experiments, with data manipulation, with experimental choices and most importantly with evaluation and analysis of results. | ||||||||
Uren per week | 4 | ||||||||
Onderwijsvorm |
werkcollege
(Lectures and practicals) |
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Toetsvorm |
opdrachten
(Final project (individual or in groups, depending on size of class). This will most likely consist of a small working system plus a report in the form of a scientific paper.) |
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Vaksoort | bachelor | ||||||||
Coördinator | Prof. Dr. M. Nissim | ||||||||
Docent(en) | Prof. Dr. M. Nissim | ||||||||
Verplichte literatuur |
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Entreevoorwaarden | Knowledge of Python is an advantage | ||||||||
Opmerkingen | |||||||||
Opgenomen in |
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