Machine Learning with Python: k-Means Clustering

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Free Online Course: Machine Learning with Python: k-Means Clustering provided by LinkedIn Learning is a comprehensive online course, which lasts for Less than 1 hour of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. Machine Learning with Python: k-Means Clustering is taught by Frederick Nwanganga.

Overview
  • 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