International Law for International Relations
Environment and Social Development
Intelligent Robot and Advanced Manufacturing
Multi-field cross-scale simulation
Critical Conservation and Revitalization of Architecture Heritage
Curating Contemporary Art: Museums, Galleries, Exhibitions and the Curator
Artificial Intelligence and Big Data
Introduction to Computer Science and Programming
Basics of Machine Learning and Data Analysis
Smart Earth
Infections and Immune Response
Healthy China Initiative and International Health Cooperation
Course Form for WHU Summer School International 2024
Course Title |
Basics of Machine Learning and Data Analysis |
机器学习的多领域应用-人工智能基础 |
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Teacher |
Sorin Istrail |
First day of classes |
2024/06/30 |
Last day of classes |
2024/07/08 |
Course Credit |
1 |
Course Description |
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Course Introduction |
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本课程为机器学习入门课程,涵盖了机器学习的基本概念和应用,课程将介绍基本的机器学习算法。我们将首先通过每个类中的一组基础算法来介绍无监督和监督机器学习算法。然后,我们将介绍这些算法在推荐系统中的应用,比如像Netflix、Spotify 和亚马逊等公司在其大数据分析软件系统中用于电影、音乐和书籍的推荐等,这类推荐系统无疑已成为当下业务的主要驱动力。 |
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Objective |
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• 理解机器学习的基本概念,并理解它们在解决实际问题中的应用; • 掌握机器学习算法和技术,并学会使用相应的工具和技术实现这些算法; • 能够运用机器学习解决实际问题,并基于机器学习技术进行模型训练和预测; • 培养数据驱动的决策能力,并能够利用机器学习技术从数据中提取有价值的信息。 |
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Assignments (essay or other forms) |
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Homework 20 single choice Final exam 20 multiple choice 作业:20道单选题 期末考试:20道多选题 |
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Text Books and Reading Materials |
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Book 1: J. Leskovec, A. Rajaraman, J. Ullman (second edition), “Mining Massive Datasets” Cambridge University Press 2019
PPTs slides: http://www.mmds.org/#ver10
Book 2: Tom Mitchel “Machine Learning”, 1997
PPTs slides: http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml http://www.cs.cmu.edu/~tom/mlbook.html
Book 3: P-N Tan, M. Steinbach, V. Kumar, “Introduction to Data Mining” (second edition), Pearson Publ., 2023
PPTs slides: https://www-users.cse.umn.edu/~kumar001/dmbook/index.php
Book 4: C. Manning, P. Raghavan, H. Schutze, “Introduction to Information Retrieval”, Cambridge University Press, 2008
PPTs slides: https://www.cs.odu.edu/~sampath/courses/w17/cs599/ |