Book Image

Time Series Analysis on AWS

By : Michaël Hoarau
Book Image

Time Series Analysis on AWS

By: Michaël Hoarau

Overview of this book

Being a business analyst and data scientist, you have to use many algorithms and approaches to prepare, process, and build ML-based applications by leveraging time series data, but you face common problems, such as not knowing which algorithm to choose or how to combine and interpret them. Amazon Web Services (AWS) provides numerous services to help you build applications fueled by artificial intelligence (AI) capabilities. This book helps you get to grips with three AWS AI/ML-managed services to enable you to deliver your desired business outcomes. The book begins with Amazon Forecast, where you’ll discover how to use time series forecasting, leveraging sophisticated statistical and machine learning algorithms to deliver business outcomes accurately. You’ll then learn to use Amazon Lookout for Equipment to build multivariate time series anomaly detection models geared toward industrial equipment and understand how it provides valuable insights to reinforce teams focused on predictive maintenance and predictive quality use cases. In the last chapters, you’ll explore Amazon Lookout for Metrics, and automatically detect and diagnose outliers in your business and operational data. By the end of this AWS book, you’ll have understood how to use the three AWS AI services effectively to perform time series analysis.
Table of Contents (20 chapters)
1
Section 1: Analyzing Time Series and Delivering Highly Accurate Forecasts with Amazon Forecast
9
Section 2: Detecting Abnormal Behavior in Multivariate Time Series with Amazon Lookout for Equipment
15
Section 3: Detecting Anomalies in Business Metrics with Amazon Lookout for Metrics

Recognizing different types of anomalies

Before we dive into Amazon Lookout for Metrics, I recommend that you read a few definitions first. If you need a refresher about what different types of anomalies look like in time series data, you can read the What are the different approaches to tackle anomaly detection? section at the beginning of Chapter 8, An Overview of Amazon Lookout for Equipment. This paragraph will give you an overview of the different types of anomalies we can find in time series data, along with a description of the different approaches we can use when building a custom outlier or anomaly detection system from scratch.

If you head over to the Amazon Lookout for Metrics home page (https://aws.amazon.com/lookout-for-metrics), you will read that it uses ML techniques to automatically detect anomalies that are defined as outliers from the norm. Amazon Lookout for Metrics looks for deviations in live or real-time univariate time series data. The keyword in this description...