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20774 Perform Cloud Data Science with Azure Machine Learning

The main purpose of this 5-day 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.

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Overview

The main purpose of this 5-day 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.

Prerequisites

In addition to their professional experience, participants who wish to attend this course should have:

  • Programming experience using R, and familiarity with common R packages
  • Knowledge of common statistical methods and data analysis best practices.
  • Basic knowledge of the Microsoft Windows operating system and its core functionality.
  • Working knowledge of relational databases.

Who Should Attend?

This course is recommended for people who wish to analyze and present data by using Azure Machine Learning. This course is also recommended for IT professionals, developers and information workers who need to support solutions based on Azure Machine Learning.

Course Outline

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

Lab: Introduction to 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

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

Lab: Managing Datasets

  • Data pre-processing
  • Handling incomplete datasets

Lab: Preparing data for use with Azure machine learning

  • Using feature engineering
  • Using feature selection

Lab: Using feature engineering and selection

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

Lab: Building Azure machine learning models

  • Using classification algorithms
  • Clustering techniques
  • Selecting algorithms

Lab: Using classification and clustering with Azure machine learning models

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

Lab: Using R and Python with Azure machine learning

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

Lab: Initializing and optimizing machine learning models

  • Deploying and publishing models
  • Consuming Experiments

Lab: Using Azure machine learning models

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

Lab: Using Cognitive Services

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

Lab: Machine Learning with HDInsight

  • 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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