关键信息
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.
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.
教师
Jiawei Han
Abel Bliss Professor
Department of Computer Science
内容设计师
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。
平台
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。
