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

Extracting the inference results

In the previous section, you let your scheduler run thrice. The results from any successful inference will be stored in the output location on S3 that you configured at the beginning of this chapter. Let's download one of these files and look at its content:

  1. Log in to your AWS console.
  2. At the top left of your console, you will see a Services drop-down menu that will display all the available AWS services. In the Storage section, look for the S3 service and click on its name to go to the S3 console.
  3. Navigate to your bucket and then to inference-data and finally to output. Each inference execution creates a new directory named after the timestamp at which the scheduler woke up.

Figure 11.19 – Inference scheduler output content

  1. In this directory, you will find a single file named results.jsonl. This is a JSON-line file. Click the checkbox next to its name and click on the Download button.
  2. ...