Course title
知能情報システム工学特別講義（データ分析の数理）   [Special Lecture on Electrical Engineering and Computer Science (Data Analysis)]
Course category	technology speciality courses	Requirement		Credit	2
Department		Year	3～4	Semester	3rd
Course type	3rd	Course code	023671
Instructor(s)
藤田 桂英, 柴原 一友, 藤本 浩司, 宮武 孝尚   [FUJITA Katsuhide, SHIBAHARA Kazutomo, FUJIMOTO Kohji, MIYATAKE Takahisa]
Facility affiliation	Graduate School of Engineering	Office	afjgxte/L1151	Email address

Course description

Learning concept and basic skill of data mining, which extracts knowledge from big data. The lecture of this course has the firsthand experiences on technology management in various corporates, and will describe actual examples from industry for case-studies, analysis and discussion.

Expected Learning

Learning concept and basic skill in extraction knowledge from big data. See the Curriculum maps.

Course schedule

Day 1(#1-#5) Data mining and cunsumption society, How to predict the future by using possibility, Basic operation of R (statistical analysis software), Report Day 2(#6-#10) What is classification tree?, How to evaluate classification trees, Linear regression, Logistic regression, Non-parametric regression Day 3(#11-#15) Neural network, Support vector machine, Probabilistic-structured model (Bayes' theorem), Report

Prerequisites

In addition to 30 hours that students spend in the class, students are recommended to prepare for and revise the lectures, spending the standard amount of time as specified by the University and using the lecture handouts as well as the references specified below.

Required Text(s) and Materials

Handout

References

Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management

Assessment/Grading

Evaluate by contributions during the classes(50%) and assignments(50%)

Message from instructor(s)

Course keywords

Classification tree, Linear regression, Logistic regression, Non-parametric regression Neural network, Support vector machine, Bayes' theorem, R (statistical analysis software)

Office hours

Remarks 1

Remarks 2

Related URL

Lecture Language

Language Subject

Last update

5/26/2021 9:39:02 AM