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.
Этот курс входит в специализацию ''Специализация Интеллектуальный анализ данных '
от партнера


Об этом курсе
Приобретаемые навыки
- Cluster Analysis
- Data Clustering Algorithms
- K-Means Clustering
- Hierarchical Clustering
от партнера

Иллинойсский университет в Урбане-Шампейне
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Сделайте шаг навстречу диплому магистра.
Программа курса: что вы изучите
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.
Module 1
Week 2
Week 3
Week 4
Course Conclusion
In the course conclusion, feel free to share any thoughts you have on this course experience.
Рецензии
- 5 stars66,41 %
- 4 stars23,40 %
- 3 stars5,59 %
- 2 stars2,03 %
- 1 star2,54 %
Лучшие отзывы о курсе АНАЛИЗ КЛАСТЕРОВ В ПРОЦЕССЕ АНАЛИЗА ДАННЫХ
Very intense and required complex thinking and programming skill
This is a very good course covering all area of clustering. The only thing I feel a little struggle is some algorithm explained too brief, I prefer some detail step by step examples.
Good course for understanding the Cluster Analysis & Algorithms, instructor is very experienced and well explained, thanks
A very good course, it gives me a general idea of how clustering algorithm work.
Специализация Интеллектуальный анализ данных : общие сведения
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp.

Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Что я получу, оформив подписку на специализацию?
Можно ли получить финансовую помощь?
Остались вопросы? Посетите Центр поддержки учащихся.