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

Generating a forecast

In Chapter 4, Training a Predictor with AutoML, and Chapter 5, Customizing Your Predictor Training, we focused on the first step of the forecasting process: looking back in historical data to establish a baseline and uncover trends that may continue in the future. In Amazon Forecast, this is done by training a predictor (your trained model). Once you have a model ready to be used, you can use Amazon Forecast to generate predictions for your time series: this is the highlighted area on the right side in the following figure:

Figure 6.1 – Amazon Forecast overview

In other words, you will use Amazon Forecast to generate future values in a timeframe beyond the last date available in your ingested dataset. In Chapter 3, Creating a Project and Ingesting Your Data, you ingested data from 2012-07-01 to 2013-06-30. You are now going to generate predictions for data starting on 2013-07-01.

In the next section, you are going to learn how...