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Time Series Analysis on AWS

Time Series Analysis on AWS

By : Hoarau
5 (5)
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Time Series Analysis on AWS

Time Series Analysis on AWS

5 (5)
By: 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)
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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

Chapter 4: Training a Predictor with AutoML

In Chapter 3, Creating a Project and Ingesting Your Data, you learned how a raw dataset obtained from a public data source could be prepared and ingested in a suitable format for Amazon Forecast. Additionally, you created your first forecasting project (which, in the service, is called a dataset group) and populated it with three datasets. These datasets included the very time series that you want to forecast and several related time series that, intuitively, will lend some predictive power to the model you are going to train.

In this chapter, you will use these ingested datasets to train a forecasting model in Amazon Forecast; this construct is called a Predictor. Following this, you will learn how to configure the training along with the impact that each configuration can have on the training duration and the quality of the results. By the end of the chapter, you will also have a sound understanding of the evaluation dashboard.

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