Forecast Flight Delays with Amazon Machine Learning

The hands-on lab is part of this learning path

Introduction to Machine Learning on AWS
course-steps 4 certification 1 lab-steps 3

Lab Steps

Logging in to the Amazon Web Services Console
Understanding the Flight Delay Data
Creating an Amazon Machine Learning Flight Datasource
Creating a Pair of Flight Delay Machine Learning Models
Inspecting the Flight Delay Datasource
Evaluating the Flight Delay Models
Forecasting Flight Delays with the Models
Validate AWS Lab

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Lab Overview

Amazon Machine Learning provides an easy-to-use interface for creating certain types of machine learning models. This Lab uses Amazon Machine Learning to create a regression model. Regression models predict a continuous variable, as opposed to a set of classes that are predicted by classification models. You will use US Department of Transportation flight data to forecast flight delays with the Amazon Machine Learning regression model. You will create two models using custom model recipes: one that can be used for long-term forecasting and one for near-term forecasting.

Lab Objectives

Upon completion of this Lab you will be able to:

  • Create and analyze the performance of regression models in Amazon Machine Learning
  • Define custom schemas and recipes for Amazon Machine Learning datasources and models
  • Make real-time predictions with Amazon Machine Learning models

Lab Prerequisites

You should be familiar with:

  • Basic S3 concepts
  • Some knowledge of machine learning concepts is beneficial, but not required

Lab Environment

Before completing the Lab instructions, the environment will look as follows:

After completing the Lab instructions, the environment should look similar to:



January 10th, 2019 - Added a validation Lab Step to check the work you perform in the Lab

About the Author

Learning paths4

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, MCSE: Cloud Platform and Infrastructure, Google Cloud Certified Associate Cloud Engineer, Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), and Linux Foundation Certified System Administrator (LFCS). He earned his Ph.D. studying design automation and enjoys all things tech.