|
Books > Computing & IT > Applications of computing > Artificial intelligence
|
Buy Now
Applied Unsupervised Learning with R - Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA (Paperback)
Loot Price: R974
Discovery Miles 9 740
|
|
|
Applied Unsupervised Learning with R - Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA (Paperback)
Expected to ship within 18 - 22 working days
|
Design clever algorithms that discover hidden patterns and draw
responses from unstructured, unlabeled data. Key Features Build
state-of-the-art algorithms that can solve your business' problems
Learn how to find hidden patterns in your data Revise key concepts
with hands-on exercises using real-world datasets Book
DescriptionStarting with the basics, Applied Unsupervised Learning
with R explains clustering methods, distribution analysis, data
encoders, and features of R that enable you to understand your data
better and get answers to your most pressing business questions.
This book begins with the most important and commonly used method
for unsupervised learning - clustering - and explains the three
main clustering algorithms - k-means, divisive, and agglomerative.
Following this, you'll study market basket analysis, kernel density
estimation, principal component analysis, and anomaly detection.
You'll be introduced to these methods using code written in R, with
further instructions on how to work with, edit, and improve R code.
To help you gain a practical understanding, the book also features
useful tips on applying these methods to real business problems,
including market segmentation and fraud detection. By working
through interesting activities, you'll explore data encoders and
latent variable models. By the end of this book, you will have a
better understanding of different anomaly detection methods, such
as outlier detection, Mahalanobis distances, and contextual and
collective anomaly detection. What you will learn Implement
clustering methods such as k-means, agglomerative, and divisive
Write code in R to analyze market segmentation and consumer
behavior Estimate distribution and probabilities of different
outcomes Implement dimension reduction using principal component
analysis Apply anomaly detection methods to identify fraud Design
algorithms with R and learn how to edit or improve code Who this
book is forApplied 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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
You might also like..
|
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
