Statistical data analysis, Advanced A

Numbering Code G-ECON31 6A613 LJ10
G-ECON31 6A613 LJ43
G-ECON31 6A613 LJ44
Year/Term 2021 ・ Second semester
Number of Credits 2 Course Type Lecture
Target Year Target Student
Language Japanese Day/Period Mon.2
Instructor name AKITA YUYA (Graduate School of Economics Professor)
Outline and Purpose of the Course The ability to organize and analyze a variety of data, extract significant or valuable information, and create models to represent or interpret data constitute an important skill in our modern age. Data is growing in scale with every passing year; the ability to process it efficiently and effectively through appropriate means is desirable. Students in this course will learn a variety of information science techniques for conducting statistical analysis or classification of or forming predictions from this data?namely, pattern recognition and machine learning?using the Python language to implement what they have learned.
Course Goals ・ To understand the theoretical background and characteristics of various approaches to pattern recognition and machine learning _x005F_x000D_ ・ To learn the processes behind Python-based techniques
Schedule and Contents Each of the following themes will as a general rule be presented two to three times, in order. Practice will be conducted using lectures and the Python language. _x005F_x000D_ The number of times and order in which themes are presented may change as appropriate depending on the state of student progress. _x005F_x000D_ _x005F_x000D_ ・ Fundamentals of pattern recognition _x005F_x000D_ ・ Clustering _x005F_x000D_ ・ Machine learning _x005F_x000D_ ・ Neural networks _x005F_x000D_ ・ Text mining
Evaluation Methods and Policy Participants will be graded on their interim and final reports (50 pts. each).
Course Requirements Applicants should have completed Statistical Data Analysis Advanced A. They should understand basic statistics and linear algebra. They should have basic knowledge of and be able to operate computers, and they should be learning the Python programming language.
Study outside of Class (preparation and review) Each class supposes that students understand the contents of the previous lectures, so students should take care to review lesson content sufficiently in advance.
Textbooks Textbooks/References Not used
References, etc. Introduced during class
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