Michaël Hoarau

Time Series Analysis on AWS (eBook, ePUB)

Learn how to build forecasting models and detect anomalies in your time series data

• Format: ePub

Produktbeschreibung

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.

Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 458
• Erscheinungstermin: 28. Februar 2022
• Englisch
• ISBN-13: 9781801814027
• Artikelnr.: 70296241

Autorenporträt

Michaël Hoarau is an AI/ML specialist solutions architect (SA) working at Amazon Web Services (AWS). He is an AWS Certified Associate SA. He previously worked as an AI/ML specialist SA at AWS and the EMEA head of data science at GE Digital. He has experience in building product quality prediction systems for multiple industries. He has used forecasting techniques to build virtual sensors for industrial production lines. He has also helped multiple customers build forecasting and anomaly detection systems to increase their business efficiency.