link 来源:www.coursera.org
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assignment 等级:入门
chat_bubble_outline 语言:英语
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关于内容

Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications.

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课程大纲

  • Week 1 - Course Orientation
    You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
  • Week 1 - Module 1
     
  • Week 2 - Week 2
     
  • Week 3 - Week 3
     
  • Week 4 - Week 4
     
  • Week 4 - Course Conclusion
    In the course conclusion, feel free to share any thoughts you have on this course experience.
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教师

Jiawei Han
Abel Bliss Professor
Department of Computer Science

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内容设计师

University of Illinois at Urbana-Champaign

伊利诺伊大学香槟分校(UIUC)成立于 1867 年。伊利诺伊大学的主校区位于芝加哥以南 200 公里处的香槟和厄巴纳双城。

根据世界大学排名中心(Center for World University Rankings)等多项排名,这所重点大学跻身全球最负盛名的大学之列,2020-21 年的全球排名为第 22 位。

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平台

Coursera

Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。

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