What Is Clustering In Data Science?| Introduction To Clustering | Data Science Tutorial |Simplilearn
About this course
This course provides an in-depth understanding of clustering methods in data science, particularly focusing on hierarchical clustering and its applications. Learners will explore clustering concepts through real-world examples, including customer segmentation and city planning, while gaining insights into various algorithms such as k-means and fuzzy c-means. The course emphasizes the importance of distance measures and terminologies like dendrograms as essential components in clustering techniques.
What you should already know
Basic knowledge of data science concepts and familiarity with mathematical principles related to distance measures in datasets.
What you will learn
By the end of the course, learners will be able to apply clustering techniques to their data analysis tasks, understand the differences between hierarchical and partial clustering, and utilize appropriate algorithms for diverse applications.