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Machine Learning with Python: k-Means Clustering

via LinkedIn Learning

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Overview

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Learn the basics of k-means clustering, one of the most popular unsupervised machine learning approaches.

Syllabus

Introduction
  • Getting started with Python and k-means clustering
  • What you should know
  • The tools you need
  • Using the exercise files
1. Understanding K-Means Clustering
  • What is clustering?
  • What is k-means clustering?
  • Choosing the right number of clusters
  • Why and when to use k-means clustering
2. Segmenting Data with K-Means Clustering
  • How to segment data with k-means clustering in Python
  • How to evaluate and visualize clusters in Python
  • How to find the right number of clusters in Python
  • How to interpret the results of k-means clustering in Python
Conclusion
  • Next steps

Taught by

Frederick Nwanganga

Reviews

4.7 rating at LinkedIn Learning based on 502 ratings

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