Welcome to the session on ‘K-Means Clustering’. In the previous session, you got a basic idea of what unsupervised learning is. You also learnt about one such unsupervised technique called clustering. Now let’s dive deeper into the concept and learn about the first common algorithm to achieve this unsupervised clustering — the K-Means algorithm.
In this session
You will learn about:
- The steps in the K-Means algorithm.
- How to graphically visualise the steps of K-Means algorithm.
- Practical considerations while using the K-Means algorithm.
Guidelines for in-module questions
The in-video and in-content questions for this module are not graded. The graded questions are given in a separate segment at the end of the session. The questions in that segment will adhere to the following guidelines:
| First Attempt Marks | Second Attempt Marks | |
| Question with 2 Attempts | 10 | 5 |
| Question with 1 Attempt | 10 | 0 |
People you will hear from in this session
Subject Matter Expert
Assistant Professor, IIIT- BThe International Institute of Information Technology, Bangalore, also known as IIIT-B, is one of India’s foremost graduate schools. Through its Integrated M.Tech., M.Tech., M.S. (Research) and PhD programs in the IT space, it focuses equally on innovation and education.
Presenter
Rohit Sharma