Applied Unsupervised Learning with R
Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and all features of R that enable you to understand your data better and get answers to all your business questions.
Offered by
Difficulty Level
Intermediate
Completion Time
10h40m
Language
English
About Book
Who Is This Book For?
Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.
Applied Unsupervised Learning with R
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 10h40m total length
Introduction to Clustering Methods
Advanced Clustering Methods
Probability Distributions
Dimension Reduction
Data Comparison Methods
Anomaly Detection
Related Resources
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