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 34  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