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This module introduces machine learning and discussed how algorithms and languages are used.
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Describe the purpose of Azure Machine Learning, and list the main features of Azure Machine Learning Studio.
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At the end of this module the student will be able to upload and explore various types of data in Azure machine learning.
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This module provides techniques to prepare datasets for use with Azure machine learning.
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This module describes how to explore and use feature engineering and selection techniques on datasets that are to be used with Azure machine learning.
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This module describes how to use regression algorithms and neural networks with Azure machine learning.
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This module describes how to use classification and clustering algorithms with Azure machine learning.
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This module describes how to use R and Python with azure machine learning and choose when to use a particular language.
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This module describes how to use hyper-parameters and multiple algorithms and models, and be able to score and evaluate models.
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This module explores how to provide end users with Azure machine learning services, and how to share data generated from Azure machine learning models.
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This module introduces the cognitive services APIs for text and image processing to create a recommendation application, and describes the use of neural networks with Azure machine learning.
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This module describes how use HDInsight with Azure machine learning.
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This module describes how to use R and R server with Azure machine learning, and explain how to deploy and configure SQL Server and support R services.
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