Welcome to the session on ‘Executing K-Means in Python’. In the previous sessions, you got a basic understanding of what clustering is and how you can use the K-Means algorithm to cluster objects. In this session, you will see the implementation of the K-Means algorithm in Python on the Online Retail case study that was introduced earlier.
In this session
You will learn about
- Data preparation
- How to make the clusters
- Decide the optimal number of clusters
- How to interpret the results
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:
People you will hear from in this session
Subject Matter Expert
Dinesh J Babu
Assistant Professor, IIIT- B
The 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.
Head Analytics and AVP Strategy, Viacom18
Presenter
Ajay Shukla
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