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

Choosing the right applications

You have successfully framed your ML project as a forecasting problem and you have collected some historical time series datasets. Is Amazon Forecast a good candidate to deliver the desired insights? Let's review some considerations that will help you understand whether Amazon Forecast is suitable for your forecasting scenario—namely, the following:

  • Latency requirements
  • Dataset requirements
  • Use-case requirements

All in all, reading through these requirements will help you define when Amazon Forecast is best suited for a given problem. You will also understand when it is not likely to be a good candidate for this. You will have some pointers on what you need to do to adjust your problem framework so that it matches Amazon Forecast's native capabilities.

Latency requirements

With Amazon Forecast, the training must happen in the cloud—if your data is not available in cloud storage such as Amazon S3, the...