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

Exporting and visualizing your predictor backtest results

In this section, you are going to explore how you can visualize the performance of the predictor that you trained by exporting and visualizing the backtest results. I will start by explaining what backtesting is and then show you how you can export and visualize the results associated with your predictor.

In the Predictor metrics section, you might have noticed an Export backtest results button in the upper-right corner of the section, as shown in the following screenshot:

Figure 4.12 – The results page: Predictor metrics

Before we click on this button, first, let's define what backtesting is in the next section.

What is backtesting?

Backtesting is a technique used in time series-oriented machine learning to tune your model parameters during training and produce accuracy metrics. To perform backtesting, Amazon Forecast splits the data that you provide into two datasets:

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