MACHINE LEARNING THEORY
- Course
- DASC510 - MACHINE LEARNING THEORY
- Department
- Data Science - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 8
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
Course Description
In this course, the concept of machine learning and its underlying probabilistic and statistical approaches will be covered extensively with a focus on the tools and techniques required for multivariate data analysis. Students taking this course are expected to have basic mathematics and Python programming background. Students completing this course will have the skills to apply regression, classification, clustering, dimensionality reduction and evaluation methods and techniques to handle uncertain data with probabilistic models. Upon completion of this course, students will be able to compare systems that can solve problems by coming up with their own rules via trial and error with systems that automatically identify patterns in data.
MACHINE LEARNING THEORY
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