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The main purpose of the course is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use of machine learning with big data tools such as HDInsight and R Services.

TARGET AUDIENCE

The primary audience for this course is people who wish to analyze and present data by using Azure Machine Learning. The secondary audience is IT professionals, Developers , and information workers who need to support solutions based on Azure machine learning.

COURSE OBJECTIVES

After completing this course, students will be able to:

•Explain machine learning, and how algorithms and languages are used

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

•Upload and explore various types of data to Azure Machine Learning

•Explore and use techniques to prepare datasets ready for use with Azure Machine Learning

•Explore and use feature engineering and selection techniques on datasets that are to be used with Azure Machine Learning

•Explore and use regression algorithms and neural networks with Azure Machine Learning

•Explore and use classification and clustering algorithms with Azure Machine Learning

•Use R and Python with Azure Machine Learning, and choose when to use a particular language

•Explore and use hyperparameters and multiple algorithms and models, and be able to score and evaluate models

•Explore how to provide end-users with Azure Machine Learning services, and how to share data generated from Azure Machine Learning models

•Explore and use the Cognitive Services APIs for text and image processing, to create a recommendation application, and describe the use of neural networks with Azure Machine Learning

•Explore and use HDInsight with Azure Machine Learning

•Explore and use R and R Server with Azure Machine Learning, and explain how to deploy and configure SQL Server to support R services

COURSE OUTLINE

1 – INTRODUCTION TO MACHINE LEARNING

What is machine learning? Introduction to machine learning algorithms Introduction to machine learning languages Lab : Introduction to machine Learning

2 – INTRODUCTION TO AZURE MACHINE LEARNING

Azure machine learning overview Introduction to Azure machine learning studio Developing and hosting Azure machine learning applications Lab : Introduction to Azure machine learning

3 – MANAGING DATASETS

Categorizing your data Importing data to Azure machine learning Exploring and transforming data in Azure machine learning Lab : Managing Datasets

4 – PREPARING DATA FOR USE WITH AZURE MACHINE LEARNING

Data pre-processing Handling incomplete datasets Lab : Preparing data for use with Azure machine learning

5 – USING FEATURE ENGINEERING AND SELECTION

Using feature engineering Using feature selection Lab : Using feature engineering and selection

6 – BUILDING AZURE MACHINE LEARNING MODELS

Azure machine learning workflows Scoring and evaluating models Using regression algorithms Using neural networks Lab : Building Azure machine learning models

7 – USING CLASSIFICATION AND CLUSTERING WITH AZURE MACHINE LEARNING MODELS

Using classification algorithms Clustering techniques Selecting algorithms Lab : Using classification and clustering with Azure machine learning models

8 – USING R AND PYTHON WITH AZURE MACHINE LEARNING

Using R Using Python Incorporating R and Python into Machine Learning experiments Lab : Using R and Python with Azure machine learning

9 – INITIALIZING AND OPTIMIZING MACHINE LEARNING MODELS

Using hyper-parameters Using multiple algorithms and models Scoring and evaluating Models Lab : Initializing and optimizing machine learning models

10 – USING AZURE MACHINE LEARNING MODELS

Deploying and publishing models Consuming Experiments Lab : Using Azure machine learning models

11 – USING COGNITIVE SERVICES

Cognitive services overview Processing language Processing images and video Recommending products Lab : Using Cognitive Services

12 – USING MACHINE LEARNING WITH HDINSIGHT

Introduction to HDInsight HDInsight cluster types HDInsight and machine learning models Lab : Machine Learning with HDInsight

13 – USING R SERVICES WITH MACHINE LEARNING

R and R server overview Using R server with machine learning Using R with SQL Server Lab : Using R services with machine learning

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