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

Summary

Although every time series looks alike (a tabular dataset indexed by time), choosing the right tools and approaches to frame a time series problem is critical to successfully leverage ML to uncover business insights.

After reading this chapter, you understand how time series can vastly differ from one another and you should have a good command of the families of preprocessing, transformation, and analysis techniques that can help derive insights from time series datasets. You also have an overview of the different AWS services and open source packages you can leverage to help you in your endeavor. After reading this chapter, you can now recognize how rich this domain is and the numerous options you have to process and analyze your time series data.

In the next three parts of this book, we are going to abstract away most of these choices and options by leveraging managed services that will do most of the heavy lifting for you. However, it is key to have a good command of these concepts to develop the right understanding of what is going on under the hood. This will also help you make the right choices whenever you have to tackle a new use case.

We will start with the most popular time series problem we want to solve with time series forecasting, with Amazon Forecast.