Perform Cloud Data Science with Azure Machine Learning

Introduction to Machine Learning

This module introduces machine learning and discussed how algorithms and languages are used.

Topics:

• What is machine learning?
• Introduction to machine learning algorithms
• Introduction to machine learning languages

Introduction to Azure Machine Learning

Describe the purpose of Azure Machine Learning, and list the main features of Azure Machine Learning Studio.

Topics:

• Azure machine learning overview
• Introduction to Azure machine learning studio
• Developing and hosting Azure machine learning applications

Managing Datasets

At the end of this module the student will be able to upload and explore various types of data in Azure machine learning.

Topics:

• Categorizing your data
• Importing data to Azure machine learning
• Exploring and transforming data in Azure machine learning

Preparing Data for use with Azure Machine Learning

This module provides techniques to prepare datasets for use with Azure machine learning.

Topics:

• Data pre-processing
• Handling incomplete datasets

Using Feature Engineering and Selection

This module describes how to explore and use feature engineering and selection techniques on datasets that are to be used with Azure machine learning.

Topics:

• Using feature engineering
• Using feature selection

Building Azure Machine Learning Models

This module describes how to use regression algorithms and neural networks with Azure machine learning.

Topics:

• Azure machine learning workflows
• Scoring and evaluating models
• Using regression algorithms
• Using neural networks

Using Classification and Clustering with Azure machine learning models

This module describes how to use classification and clustering algorithms with Azure machine learning.

Topics:

• Using classification algorithms
• Clustering techniques
• Selecting algorithms

Using R and Python with Azure Machine Learning

This module describes how to use R and Python with azure machine learning and choose when to use a particular language.

Topics:

• Using R
• Using Python
• Incorporating R and Python into Machine Learning experiments

Initializing and Optimizing Machine Learning Models

This module describes how to use hyper-parameters and multiple algorithms and models, and be able to score and evaluate models.

Topics:

• Using hyper-parameters
• Using multiple algorithms and models
• Scoring and evaluating Models

Using Azure Machine Learning Models

This module explores how to provide end users with Azure machine learning services, and how to share data generated from Azure machine learning models.

Topics:

• Deploying and publishing models
• Consuming Experiments

Using Cognitive Services

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.

Topics:

• Cognitive services overview
• Processing language
• Processing images and video
• Recommending products

Using Machine Learning with HDInsight

This module describes how use HDInsight with Azure machine learning.

Topics:

• Introduction to HDInsight
• HDInsight cluster types
• HDInsight and machine learning models

Using R Services with Machine Learning

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.

Topics:

• R and R server overview
• Using R server with machine learning
• Using R with SQL Server