In this book, you will learn how anomaly detection can be used to solve business problems. You will explore how anomaly detection techniques can be used to address practical use cases and address real-life problems in the business landscape. Every business and use case is different, so while we cannot copy and paste code and build a successful model to detect anomalies in any dataset, this book will cover many use cases with hands-on coding exercises to give you an idea of the possibilities and concepts behind the thought process. All the code examples in the book are presented in Python 3-8. We choose Python because it is truly the best language for data science, with a plethora of packages and integrations with scikit-learn, deep learning libraries, etc. We will start by introducing anomaly detection, and then we will look at legacy methods of detecting anomalies that have been used for decades.
