Clustering | Data Mining | Machine Learning

Learn the fundamental concepts and techniques of clustering, a key data mining and machine learning method for grouping similar objects. Hands-on exercises and real-world projects included.

Introduction

This course covers the fundamental concepts and techniques of clustering, which is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar to each other than to those in other groups (clusters).

Highlights

• Covers various clustering algorithms such as k-means, hierarchical clustering, and density-based clustering
• Discusses the evaluation and comparison of clustering results
• Includes hands-on exercises and projects using real-world datasets

Recommendation

This course is recommended for students and professionals interested in data mining, machine learning, and unsupervised learning. It provides a solid foundation in clustering techniques and their practical applications, making it a valuable resource for those working with large and complex datasets.

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