Packt+ | Advance your knowledge in tech

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Applied Unsupervised Learning with R

You're reading from Applied Unsupervised Learning with R Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA

Product type Paperback

Published in Mar 2019

Publisher

ISBN-13 9781789956399

Length 320 pages

Edition 1st Edition

Languages

R

Concepts

Machine Learning

Authors (2):

Bradford Tuckfield

Alok Malik

View More author details

Table of Contents (9) Chapters

Applied Unsupervised Learning with R

Preface

1. Introduction to Clustering Methods FREE CHAPTER

2. Advanced Clustering Methods

3. Probability Distributions

4. Dimension Reduction

5. Data Comparison Methods

6. Anomaly Detection

Appendix

Chapter 6. Anomaly Detection

Note

Learning Objectives

By the end of this chapter, you will be able to:

Use parametric and non-parametric methods to find outliers in univariate and multivariate data
Use data transformations to identify outliers in univariate and multivariate data
Work with Mahalanobis distances
Improve anomaly detection performance by incorporating a model of seasonality

Note

In this chapter, we will have a look at different anomaly detection techniques.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

Alok Malik

Alok Malik

Alok Malik is a data scientist based in India. He has previously worked on creating and deploying unsupervised learning solutions in fields such as finance, cryptocurrency trading, logistics, and natural language processing. He has a bachelor's degree in technology from the Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, where he studied electronics and communication engineering.

See other products by Alok Malik

Bradford Tuckfield

Bradford Tuckfield

Bradford Tuckfield has designed and implemented data science solutions for firms in a variety of industries. He studied math for his bachelor's degree and economics for his Ph.D. He has written for scholarly journals and the popular press, on topics including linear algebra, psychology, and public policy.

See other products by Bradford Tuckfield

Other recommended products

Related to this chapter

Machine Learning with R Cookbook

Machine Learning with R Cookbook

The R language is a powerful open source functional programming language. At its core, R is a statistical language that provides impressive tools to analyze data and create high-level graphics. This book covers the basics of R by setting up a user-friendly programming environment and programming ETL in R. Data exploration examples are provided that demonstrate how powerful data visualisation and machine learning is in discovering hidden relationships. You will also explore air quality data, steps to fix the missing values and visualising the same. You will then dive into important machine learning topics, including data classification, regression, survival analysis, time series analysis, clustering association rule mining, and dimension reduction.This book will include the latest code and examples based on R 3.3 and above—updated for better computation, accuracy, and speed with R.

Oct 2017 19h 4m

Applied Unsupervised Learning with Python

Applied Unsupervised Learning with Python

Starting with the basics, Applied Unsupervised Learning with Python explains various techniques that you can apply to your data using the powerful Python libraries so that your unlabeled data reveals solutions to all your business questions.

May 2019 16h 4m

Applied Unsupervised Learning with Python

Applied Unsupervised Learning with Python

Starting with the basics, Applied Unsupervised Learning with Python explains various techniques that you can apply to your data using the powerful Python libraries so that your unlabeled data reveals solutions to all your business questions.

May 2019 16h 4m

The Unsupervised Learning Workshop

The Unsupervised Learning Workshop

With the help of engaging practical activities, The Unsupervised Learning Workshop teaches you how to apply unsupervised machine learning algorithms on enormous, cluttered datasets. You'll learn the best techniques and approaches and work on real-time datasets with this hands-on guide for beginners.

Jul 2020 18h 20m

The Unsupervised Learning Workshop

The Unsupervised Learning Workshop

With the help of engaging practical activities, The Unsupervised Learning Workshop teaches you how to apply unsupervised machine learning algorithms on enormous, cluttered datasets. You'll learn the best techniques and approaches and work on real-time datasets with this hands-on guide for beginners.

Jul 2020 18h 20m

The Unsupervised Learning Workshop

The Unsupervised Learning Workshop

With the help of engaging practical activities, The Unsupervised Learning Workshop teaches you how to apply unsupervised machine learning algorithms on enormous, cluttered datasets. You'll learn the best techniques and approaches and work on real-time datasets with this hands-on guide for beginners.

Jul 2020 18h 20m

The Unsupervised Learning Workshop

The Unsupervised Learning Workshop

With the help of engaging practical activities, The Unsupervised Learning Workshop teaches you how to apply unsupervised machine learning algorithms on enormous, cluttered datasets. You'll learn the best techniques and approaches and work on real-time datasets with this hands-on guide for beginners.

Jul 2020 18h 20m

The Unsupervised Learning Workshop

The Unsupervised Learning Workshop

With the help of engaging practical activities, The Unsupervised Learning Workshop teaches you how to apply unsupervised machine learning algorithms on enormous, cluttered datasets. You'll learn the best techniques and approaches and work on real-time datasets with this hands-on guide for beginners.

Jul 2020 18h 20m

The Unsupervised Learning Workshop

The Unsupervised Learning Workshop

With the help of engaging practical activities, The Unsupervised Learning Workshop teaches you how to apply unsupervised machine learning algorithms on enormous, cluttered datasets. You'll learn the best techniques and approaches and work on real-time datasets with this hands-on guide for beginners.

Jul 2020 18h 20m

Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

This book is an introduction to data mining and its practical demonstration of working with real-world data sets. With this book, you will be able to extract useful insights using common Python libraries. You will also learn key stages like data loading, cleaning, analysis, visualization to build an efficient data mining pipeline.

Apr 2019 6h 16m

Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

This book is an introduction to data mining and its practical demonstration of working with real-world data sets. With this book, you will be able to extract useful insights using common Python libraries. You will also learn key stages like data loading, cleaning, analysis, visualization to build an efficient data mining pipeline.

Apr 2019 6h 16m

Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

This book is an introduction to data mining and its practical demonstration of working with real-world data sets. With this book, you will be able to extract useful insights using common Python libraries. You will also learn key stages like data loading, cleaning, analysis, visualization to build an efficient data mining pipeline.

Apr 2019 6h 16m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m