How to Build a Predictive Analytics Model to Foresee Flight Delays – SlashdotMedia AdOps Asset Management

How to Build a Predictive Analytics Model to Foresee Flight Delays

This tutorial describes how data scientists and developers can build an application to predict flight delays. The app uses machine learning (Spark MLlib), fueled by publicly available airplane flight data and enriched with weather data, to predict flight delays due to weather conditions. In the event that a delay is likely, the app can also help determine the degree to which the flight will be delayed. To build the app, you will learn how to use a Get-Build-Analyze methodology and the IBM® Analytics for Apache® Spark™ service, which includes an interactive Jupyter Notebook. Learn how to:

  • Collect data from various sources, including weather and flight patterns.
  • Build the data collected, and test a predictive model.
  • Analyze the data for business advantage, and quantify the impact of weather on flight delays.

Get started building this flight prediction application, and gain inspiration for your next data science projects.

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