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.
At the end of this workshop, you will be better able to build a complete machine learning model in Azure Databricks for predicting if an upcoming flight will experience delays. In addition, you will learn to store the trained model in Azure Machine Learning Model Management, then deploy to Docker containers for scalable on-demand predictions, use Azure Data Factory (ADF) for data movement and operationalizing ML scoring, summarize data with Azure Databricks and Spark SQL, and visualize batch predictions on a map using Power BI.
This workshop is intended for Cloud Architects and IT professionals who have architectural expertise of infrastructure and solutions design in cloud technologies and want to learn more about Azure and Azure services as described in the ‘About this Course’ and ‘At Course Completion’ areas. Those attending this workshop should also be experienced in other non-Microsoft cloud technologies, meet the course prerequisites, and want to cross-train on Azure.
Whiteboard Design Session – Big data and visualization
- Review the customer case study
- Design a proof of concept solution
- Present the solution
Hands-on Lab – Big data and visualization
- Build a Machine Learning Model
- Setup Azure Data Factory
- Deploy your machine learning model with Azure ML
- Develop a data factory pipeline for data movement
- Operationalize ML scoring with Azure Databricks and Data Factory
- Summarize data using Azure Databricks
- Visualizing in Power BI Desktop
- Deploy intelligent web app