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

In this chapter, you learned about the tools Amazon Lookout for Metrics gives you to analyze the anomalies detected by a detector. In particular, you learned how to use the Anomalies dashboard and how to provide feedback to the service when an anomaly is detected.

This chapter was also important in helping you understand how to configure a detector in continuous mode to enable live data monitoring. You also read about using complementary content to make the service easier to use by delivering alerts in a human-readable format, making these insights even more actionable.

This is the last chapter of this section: by now, you should have a complete understanding of Amazon Lookout for Metrics and know how you can use it to perform anomaly detection on your business metrics.

You have now reached the end of this book: I hope you have enjoyed discovering what you can do with time series data using different AWS services and that you learned enough to help you get started...