Predicting Time-Series Data With Amazon Forecast

Lab Steps

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Logging in to the Amazon Web Services Console
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Preparing the Amazon Forecast Time-Series Dataset
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Training a Time-Series Model in Amazon Forecast Using AWS CLI
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Creating a Forecast
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Creating a Forecast Export

Ready for the real environment experience?

DifficultyBeginner
Time Limit1h 40m
Students95
Ratings
4.3/5
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Description

Amazon Forecast is a fully managed machine learning service for time-series forecasting. Amazon Forecast uses the same technology as Amazon.com. Accurate forecasting can drive efficiencies and improve business operations. Common examples of time-series data include web traffic and item demand at retail. The data you will use in this lab relates to power consumption data for ten individual households.

 Warning: This lab involves training a model and forecasting which both require around 20 minutes to complete. It is best to perform this lab when you are not constrained by time.

Learning Objectives

Upon completion of this beginner level lab, you will be able to:

  • Understand the main components of Amazon Forecast
  • Use Amazon Forecast to forecast structured time-series data
  • Explain the trade-offs involved with some key Amazon Forecast settings
  • Export Forecast data to CSV files

Intended Audience

  • Those interested in gaining insights from their time-series data
  • Data Scientists
  • Machine Learning Engineers

Prerequisites

Familiarity with the following will be beneficial but is not required:

  • Machine learning

The following content can be used to fulfill the prerequisite and obtain a broad understanding of machine learning and its applications:

Updates

January 14th, 2022 - Replaced Forecast Lookup (removed by AWS) with a Forecast Export job lab step

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About the Author
Students138133
Labs206
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Logan has been involved in software development and research since 2007 and has been in the cloud since 2012. He is an AWS Certified DevOps Engineer - Professional, AWS Certified Solutions Architect - Professional, Microsoft Certified Azure Solutions Architect Expert, MCSE: Cloud Platform and Infrastructure, Google Cloud Certified Associate Cloud Engineer, Certified Kubernetes Security Specialist (CKS), Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), and Certified OpenStack Administrator (COA). He earned his Ph.D. studying design automation and enjoys all things tech.