Book Image

Scala Machine Learning Projects

Book Image

Scala Machine Learning Projects

Overview of this book

Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment.
Table of Contents (17 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Outlier and anomaly detection


Anomalies are the unusual and unexpected patterns in an observed world. Thus analyzing, identifying, understanding, and predicting anomalies from seen and unseen data is one of the most important task in data mining. Therefore, detecting anomalies allows extracting critical information from data which then can be used for numerous applications.

While anomaly is a generally accepted term, other synonyms, such as outliers, discordant observations, exceptions, aberrations, surprises, peculiarities or contaminants, are often used in different application domains. In particular, anomalies and outliers are often used interchangeably. Anomaly detection finds extensive use in fraud detection for credit cards, insurance or health care, intrusion detection for cyber-security, fault detection in safety critical systems, and military surveillance for enemy activities.

The importance of anomaly detection stems from the fact that for a variety of application domains anomalies...