2022年 濱上担当講義コンテンツサイト
さぁ、はじめましょう
本サイトでは理工学部数物電子情報系学科電子情報システムEP提供講義のうち，濱上担当分の講義のビデオと関連のコンテンツを配信しています。2022年度は基本的に対面講義ですが，講義内容の理解に資する参考情報の提示と講義資料の配布場所として活用していきます。各リソースへのアクセスに必要なパスワードは授業支援システムからお知らせしています。履修登録をしてあるの各講義のページに入って受講をしてください
This site provides videos and related contents of lectures given by Prof. Hamagami in the Department of Mathematics, Physics, Electronics and Informatics of the Faculty of Science and Engineering. Although the lectures in FY2022 are basically face-to-face lectures, this site will be used to present reference information and distribute lecture materials that contribute to the understanding of the lecture content. Passwords required to access each resource will be provided through the class support system. Please register for the course and enter the page for each lecture to take the course.
本サイトの動画や資料は受講者用の限られた範囲で閲覧されることを目的にしています。意図的にダウンロードを行ったあと，2次的利用や公開をした場合は著作権上の違法行為とみなす場合があります。The videos and contents in this site are intended to be viewed on limited for registered students. Please be careful not to make secondary use of the materials or publish them to the public, as this would cause copyright issues.
GraduateSchool of Sci.and Eng.(大学院理工学府）
THURsDAY 2(10:30～)
All instructions and announcements required for this lecture will be provided by LMS. If you are unable to register in the LMS, please contact me directly via mail. Click on the above image above to watch the videos of each lecture (passward you can get it from LMS required).
One of the most interesting features of intelligent systems is that it lies on the boundary of several academic disciplines, computer sciences, statistics, mathematics, and engineering. Over the past ten years, this inherently multi-disciplinary, from finance to biology and medicine to physics and chemistry and beyond, has been embraced and understood, with many benefits for researchers in the field.
Intelligent systems are usually studied as part of artificial intelligence (AI), which puts it firmly in computer science, and given the focus on the algorithm it certainly fits there. Especially, machine learning (ML), which is about making computer modify or adapt their actions (where these actions are making predictions, or controlling a robot) can be applied varies even more widely area.
The objective of this class is to lecture you modern AI approach with a central focus on several useful ML algorithms and theories and related matters. You can learn about the basic techniques and tricks of ML, and would apply them to your study or work.
理工学部
火曜日2限(10:30～）
ソフト・コンピューティングとは，不確実性を許容することで扱いやすさ・頑健性・低コスト性などを目指す知的情報処理の考え方です。その技術は，機械学習・人工知能・最適化・ファジイ・メタヒューリスティクスなど多岐にわたります。本講義ではソフト・コンピューティングの考え方と理論・技法を学ぶとともに，具体的アルゴリズムの理解によって，さまざまな工学分野に表れる問題解決の方法論とシステム構築方法を学びます。
