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

Preparing a dataset for forecasting purposes

Throughout this chapter and the remaining chapters of this part, we are going to focus on an energy consumption dataset. The problem we want to solve is the following:

Predicting the daily electricity consumption of a household in London for the following month.

In this section, we are going to detail the following steps:

  1. Preparing the raw dataset in a format ready to be used by Amazon Forecast. If you have downloaded the already prepared dataset as mentioned in the technical requirements at the beginning of this chapter, this part is optional and you can go directly to the second step.
  2. Upload your prepared CSV files to Amazon Simple Storage Service (S3) for storage: Amazon S3 lets you store files and is often used as a file data store for many AWS services such as Amazon Forecast.
  3. Authorize Amazon Forecast to access your data in Amazon S3: this is optional as you can let Amazon Forecast do it for you while you ingest...