Course title
1M5240001
Intelligent Systems

 YASUMURA Yoshiaki Click to show questionnaire result at 2019
Course content
As an enormous amount of data like a Web data can easily acquired, intelligent systems that can process such data are required. This lecture presents fundamental technology for creating intelligent systems, and introduces actual intelligent systems. Basic technologies of intelligent systems such as machine learning, agents, and natural language processing, are discussed.
Purpose of class
The purpose of this class is to understand basic technology of artificial intelligence, especially machine learning and natural language processing.
Goals and objectives
  1. Students can understand basic technology and concepts of intelligent systems
  2. Students can understand basic technology of machine learning.
  3. Students can understand basic technology of natural language processing and agents
Language
Japanese
Class schedule

 Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1． Introduction
Intelligent systems 		Review intelligent systems 60minutes
2． Machine Learning (1)
Nearest Neighbor 		Review Nearest Neighbor 200minutes
3． Machine Learning (2)
Version Space 		Review version space 200minutes
4． Machine Learning (3)
Decision Tree 		Review Decision Tree 200minutes
5． Machine Learning (4)
Support Vector Machine
Ensemble Learning 		Review Support Vector Machine 200minutes
6． Machine Learning (5)
Clastering
Semi-supervised Learning 		Review clustering 200minutes
7． Machine Learning (6)
Neural Network 		Review neural network 200minutes
8． Machine Learning (7)
Deep Learning 		Review deep learning 200minutes
9． Machine Learning (6)
Reinforcement Learning 		Review reinforcement learning 200minutes
10． Natural Language Processing (1)
Morphological Analysis
　Syntactic Analysis 		Review Syntactic Analysis 200minutes
11． Natural Language Processing (2)
Natural language processing by neural network 		Review natural language processing by neural network 200minutes
12． Machine translation Review machine translation 200minutes
13． GAN Review GAN 200minutes
14． Application System Review application system 200minutes
Total. - - 2660minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

 Report Total.
1. 20% 20%
2. 50% 50%
3. 30% 30%
Total. 100% -
Evaluation method and criteria
Reports 100%
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback in the class
Textbooks and reference materials
Reference materials are instructed by the teachar.
Prerequisites
Nothing
Office hours and How to contact professors for questions
  • Wednesday lunch break
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Non-social and professional independence development course
Active-learning course
N/A
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
N/A
Education related SDGs:the Sustainable Development Goals
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Sat Sep 09 05:53:25 JST 2023