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Abstract

Workshop

In this workshop, you will deploy a web app using Machine Learning (ML) to predict travel delays given flight delay data and weather conditions. Plan a bulk data import operation, followed by preparation, such as cleaning and manipulating the data for testing, and training your Machine Learning model.

By attending this workshop, you will be better able to build a complete Azure Machine Learning (ML) model for predicting if an upcoming flight will experience delays. In addition, you will learn to:

  • Integrate the Azure ML web service in a Web App for both one at a time and batch predictions

  • Use Azure Data Factory (ADF) for data movement and operationalizing ML scoring

  • Summarize data with HDInsight and Spark SQL

  • Visualize batch predictions on a map using Power BI

Whiteboard Design Session

TBD

Hand-on Lab

This hands-on lab is designed to provide exposure to many of Microsoft's transformative line of business applications built using Microsoft big data and advanced analytics. The goal is to show an end-to-end solution, leveraging many of these technologies, but not necessarily doing work in every component possible. The lab architecture is below and includes:

  • Azure Machine Learning (Azure ML)

  • Azure Data Factory (ADF)

  • Azure Storage

  • HDInsight Spark

  • Power BI Desktop

  • Azure App Service

Azure services and related products

  • Azure SQL Data Warehouse
  • Azure ML
  • Azure Storage
  • Azure Active Directory
  • Power BI
  • HDInsight Spark
  • Web Apps

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.