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

Identifying suitable metrics for monitoring

You have successfully framed your ML project as an anomaly or outlier detection problem and you may have collected some historical time series datasets. Is Amazon Lookout for Metrics a good candidate to deliver your desired insights? Let's review some considerations that will help you understand whether Amazon Lookout for Metrics is suitable for your anomaly detection scenario, namely, the following:

  • Dataset requirements
  • Use case requirements

Dataset requirements

Unlike many other AI services (within AWS or not), Amazon Lookout for Metrics can get started without any data points: you won't receive any detected anomalies until there is enough information to perform a cold start detection (for instance, if your data has daily intervals, you will need to wait for at least 14 days to start receiving inference results from Amazon Lookout for Metrics) but you can start building your pipeline and your applications...