Azure Machine Learning Core Skills (1 day)
Azure Machine Learning is Microsoft's primary tool for predictive analytics. This course is designed to take you through the most important components of Azure Machine Learning, with just the right amount of depth, within a single day.
The course is most suitable for developers and BI professionals that need to learn to work with Azure Machine Learning. Existing knowledge of machine learning is not essential to complete the labs as full detailed instructions are provided.
In the course, you'll see how Azure Machine Learning lets you load your data and transform it for analysis, using a variety of algorithms and techniques. You'll see how common experiments are created and published.
Note that attendees for this course need to provide their own laptop computer and need to have an Azure subscription to use during the labs. Most students can use a trial Azure subscription or access Azure benefits from an MSDN subscription. Upon booking, we will send you details of how to set up a subscription if you do not already have one.
|CITY||DATES||COURSE PRICE||EARLY BIRD PRICE|
|On-demand||Please contact us|
|DAY 1||ML201||INTRODUCTION TO AZURE MACHINE LEARNING|
|Introduction to Machine Learning|
|Evaluating Supervised vs Unsupervised Learning|
|Working with Azure Machine Learning|
|LAB: Introduction to Azure Machine Learning|
|DAY 1||ML202||CREATING AND RUNNING AZURE MACHINE LEARNING EXPERIMENTS|
|Defining the Problem|
|Creating and Running an Experiment|
|LAB: Creating and Running Azure Machine Learning Experiments|
|DAY 1||ML203||PRACTICAL APPLICATIONS OF MACHINE LEARNING|
|Understanding Statistical and Machine Learning Algorithms|
|Implementing Common Machine Learning Models|
|Integration with the R Language|
|LAB: Practical Applications of Machine Learning|
|DAY 1||ML204||PUBLISHING, ACCESSING, AND MONETIZING MACHINE LEARNING WEB SERVICES|
|Publishing Experiments as Web Services|
|Accessing Machine Learning Web Services|
|Monetizing Machine Learning in the Azure Data Market|
|LAB: Publishing and Accessing Experiments|