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Introduction to Clustering


We will look at the fundamental concept of clustering, different types of clustering methods, and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to find groups of similar objects.

What you’ll learn

  • What is clustering?
  • Clustering weaknesses
  • Types of clustering methods: Centroid-based clustering, Connectivity-based clustering, Distribution-based clustering, and Density-based clustering
Arham Akheel
Arham Akheel

Sr. Solutions Architect at Data Science Dojo

Arham holds a Masters degree in Technology Management from Texas A&M University and has a background of managing information systems.

We are looking for passionate people willing to cultivate and inspire the next generation of leaders in tech, business, and data science. If you are one of them get in touch with us!