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Private / Corporate Training
Tell us a little about yourself:
Course Description
In this whiteboard design session, you will work with a group to design and implement a solution that combines Azure Databricks with Azure Machine Learning service to build, train and deploy the machine learning and deep learning models. In this Microsoft Azure Machine Learning Workshop, you will learn how to use automated machine learning, model lifecycle management from training to deployment, in batch and real-time inferencing scenarios, and construct deep learning models for Natural Language Processing (NLP) in text classification and forecasting against time-series data. Finally, you’ll learn to compare data with PyTorch and Keras for deep learning.
Objectives
After completing this Azure Cloud Machine Learning course, students will understand:
- The capabilities and implementation solutions of Azure Machine Learning and Azure Databricks.
Audience
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.
Prerequisites
There are no prerequisites for this course.
Content
Module 1: Whiteboard Design Session - Machine Learning
Lessons
- Review the customer case study
- Design a proof of concept solution
- Present the solution
Module 2: Hands-on lab - Machine Learning
Lessons
- Creating a forecast model using automated machine learning
- Understanding the automated ML generated forecast model using model explainability
- Creating a deep learning model (RNN) for time series data and registering the model
- Using a forecast model for scoring of streaming telemetry
- Creating a deep learning text classification model
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