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

How does Amazon Forecast work?

To build forecasting models, Amazon Forecast deals with the following concepts and resources:

  • Datasets: A dataset is a container to host your data. Amazon Forecast algorithms use these datasets to train its models. Each dataset is defined by a schema whereby you can define the columns and their types. Amazon Forecast includes several domains with predefined schemas to help you get started.
  • Dataset groups: Amazon Forecast algorithms can leverage several datasets to train a model. A dataset group is a container that packages a group of datasets used together to train a forecasting model.
  • Featurization: The featurization configuration lets you specify parameters to transform the data. This is where you specify a null-value filling strategy to apply to the different variables of your dataset.
  • Algorithms: Amazon Forecast has access to multiple algorithms including statistical algorithms (ARIMA, ETS, Prophet, and NPTS) and DL algorithms...