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Principles of Data Science

You're reading from   Principles of Data Science Understand, analyze, and predict data using Machine Learning concepts and tools

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789804546
Length 424 pages
Edition 2nd Edition
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Authors (3):
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Sunil Kakade Sunil Kakade
Author Profile Icon Sunil Kakade
Sunil Kakade
Sinan Ozdemir Sinan Ozdemir
Author Profile Icon Sinan Ozdemir
Sinan Ozdemir
Marco Tibaldeschi Marco Tibaldeschi
Author Profile Icon Marco Tibaldeschi
Marco Tibaldeschi
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Toc

Table of Contents (17) Chapters Close

Preface 1. How to Sound Like a Data Scientist FREE CHAPTER 2. Types of Data 3. The Five Steps of Data Science 4. Basic Mathematics 5. Impossible or Improbable - A Gentle Introduction to Probability 6. Advanced Probability 7. Basic Statistics 8. Advanced Statistics 9. Communicating Data 10. How to Tell If Your Toaster Is Learning – Machine Learning Essentials 11. Predictions Don't Grow on Trees - or Do They? 12. Beyond the Essentials 13. Case Studies 14. Building Machine Learning Models with Azure Databricks and Azure Machine Learning service Other Books You May Enjoy Index

k-means clustering

k-means clustering is our first example of an unsupervised machine learning model. Remember this means that we are not making predictions; instead, we are trying to extract structure from seemingly unstructured data.

Clustering is a family of unsupervised machine learning models that attempt to group data points into clusters with centroids.

Note

Definition

Cluster: This is a group of data points that behave similarly.Centroid: This is the center of a cluster. It can be thought of as an average point in the cluster.

The preceding definition can be quite vague, but it becomes specific when narrowed down to specific domains. For example, online shoppers who behave similarly might shop for similar things or at similar shops, whereas similar software companies might make comparable software at comparable prices.

Here is a visualization of clusters of points:

k-means clustering

In the preceding diagram, our human brains can very easily see the difference between the four clusters. We can see that...

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