Cluster Analysis Online Courses & Certifications
Cluster analysis is a technique used in data mining and machine learning to group similar data points together based on their intrinsic characteristics or patterns. It involves partitioning a dataset into subsets, or clusters, in a way that data points within each cluster are more similar to each other than to those in other clusters. Cluster analysis helps uncover hidden patterns, similarities, and structures within data, and it is widely used in various fields such as marketing, biology, customer segmentation, image recognition, and anomaly detection.
Cluster analysis is an exploratory technique that can reveal underlying patterns and groupings in datasets. It is particularly useful for unsupervised learning scenarios when there is no prior knowledge about the groupings within the data. By identifying clusters, it enables data analysts and researchers to gain insights, make data-driven decisions, and tailor strategies based on the characteristics of different groups within the data.
In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.