Hiroshima University Syllabus

Back to syllabus main page
Japanese
Academic Year 2022Year School/Graduate School Common Graduate Courses (Doctoral Course)
Lecture Code 8E550202 Subject Classification Common Graduate Courses
Subject Name パターン認識と機械学習
Subject Name
(Katakana)
パターンニンシキトキカイガクシュウ
Subject Name in
English
Pattern Recognition and Machine Learning
Instructor AKASE DAI
Instructor
(Katakana)
アカセ ダイ
Campus Across Campuses (videoconferencing, etc.) Semester/Term 1st-Year,  Second Semester,  4Term
Days, Periods, and Classrooms (4T) Inte:Online
Lesson Style Lecture Lesson Style
(More Details)
 
Video Lecture 
Credits 2.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 5 : Graduate Basic
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 02 : Information Science
Eligible Students
Keywords machine learning, deep learning, python 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
This course is one of the elective subjects, in "Career Development and Data Literacy Courses", Common Graduate Courses that aims to learn about the development of the current social systems, to gain knowledge needed for the future, to specifically tackle the challenges facing modern society and to acquire the ability to use knowledge and skills. 
Criterion referenced
Evaluation
 
Class Objectives
/Class Outline
This course offers students the opportunity to learn machine learning to do python exercises. 
Class Schedule Introduction
Machine Learning
Supervised Learning
Unsupervised Learning
Deep Learning
Reinforcement Learning

Assignments 
Text/Reference
Books,etc.
Not Specified. 
PC or AV used in
Class,etc.
 
(More Details) Lecture Videos 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
Students can view lecture videos any time. 
Requirements  
Grading Method Assignments 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message  
Other   
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
Back to syllabus main page