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

Chapter 12: Reducing Time to Insights for Anomaly Detections

In the previous chapters, you learned how to prepare multivariate datasets, how to train and evaluate an anomaly detection model, and how to configure an inference scheduler. To get the most from Amazon Lookout for Equipment, you can partner with a data engineer or a data scientist who will help you improve your model performance and go further in the post-processing of results.

The main objectives of this chapter are to point you in the right direction to visualize and monitor your models. This will be very valuable to detect any drift that would trigger either retraining or further investigation. In addition, you will learn how to build an automation pipeline, which will be critical to iterate as fast as possible without having to manually navigate through multiple console screens.

In this chapter, we're going to cover the following main topics:

  • Improving your model's accuracy
  • Processing the...