| Description |
1 online resource (459 pages) |
| Contents |
Table of Contents An Overview of Time Series Analysis An Overview of Amazon Forecast Creating a Project and Ingesting Your Data Training a Predictor with AutoML Customizing Your Predictor Training Generating New Forecasts Improving and Scaling Your Forecast Strategy An Overview of Amazon Lookout for Equipment Creating a Dataset and Ingesting Your Data Training and Evaluating a Model Scheduling Regular Inferences Reducing Time to Insights for Anomaly Detections An Overview of Amazon Lookout for Metrics Creating and Activating a Detector Viewing Anomalies and Providing Feedback |
| Summary |
Leverage AWS AI/ML managed services to generate value from your time series data Key Features Solve modern time series analysis problems such as forecasting and anomaly detection Gain a solid understanding of AWS AI/ML managed services and apply them to your business problems Explore different algorithms to build applications that leverage time series data Book Description 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. What you will learn Understand how time series data differs from other types of data Explore the key challenges that can be solved using time series data Forecast future values of business metrics using Amazon Forecast Detect anomalies and deliver forewarnings using Lookout for Equipment Detect anomalies in business metrics using Amazon Lookout for Metrics Visualize your predictions to reduce the time to extract insights Who this book is for If you're a data analyst, business analyst, or data scientist looking to analyze time series data effectively for solving business problems, this is the book for you. Basic statistics knowledge is assumed, but no machine learning knowledge is necessary. Prior experience with time series data and how it relates to various business problems will help you get the most out of this book. This guide will also help machine learning practitioners find new ways to leverage their skills to build effective time series-based applications |
| Notes |
Print version record |
| Subject |
Amazon Web Services (Firm)
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| SUBJECT |
Amazon Web Services (Firm) fast (OCoLC)fst01974501 |
| Subject |
Industrial management -- Statistical methods -- Computer programs
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Decision making -- Computer programs
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Decision making -- Computer programs.
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Industrial management -- Statistical methods -- Computer programs.
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| Form |
Electronic book
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| ISBN |
1801814023 |
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9781801814027 |
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