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 how Amazon Forecast organizes the datasets it needs to train a model. You also developed a good understanding of the dataset we are going to use throughout this part dedicated to forecasting and got your first hands-on experience of Amazon Forecast, as you learned how to create a forecasting project (called a dataset group in the service terminology) and how to ingest your CSV files into the appropriate datasets. You also got to learn how to use some related services, such as Amazon S3 (where we stored our CSV datasets) and AWS IAM (where we define a role to securely give access to your data to Amazon Forecast).

After reading this chapter, you will have developed a good understanding of the way Amazon Forecast requires the different datasets it needs to be structured. I recommend that you spend time understanding how each type of dataset is used by the service and which fields are actually expected from each file.

In the next chapter, we are...