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Software Assurance - Бесплатные курсы обучения по ваучерам
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Авторские курсы Microsoft
Microsoft Windows Server 2012 R2 / 2016
Microsoft Windows 10 / 8.1
Облачные технологии: Microsoft Windows Azure, Private Cloud, Office 365
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Microsoft System Center
Microsoft Lync Server 2013 / Skype for business 2015
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Вечернее обучение
Условия обучения

Курс 20774: Perform Cloud Data Science with Azure Machine Learning

Цена для физических лиц, р.: 29900
Цена для юридических лиц, р.: 30900
Цена вебинара для физических лиц, р.: 28900
Цена вебинара для юридических лиц, р.: 28900

Продолжительность курса (дней): 5

Даты (день):

Даты (вечер):

Курс готовит к тестам:

Цель:

Необходимая подготовка:

Предварительный тест:

Результат:

План курса:

20774A

Module 1: Introduction to Machine Learning

  • What is machine learning?
  • Introduction to machine learning algorithms
  • Introduction to machine learning languages
  • Lab : Introduction to machine Learning
    • Sign up for Azure machine learning studio account
    • View a simple experiment from gallery
    • Evaluate an experiment

Module 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
    • Explore the Azure machine learning studio workspace
    • Clone and run a simple experiment
    • Clone an experiment, make some simple changes, and run the experiment

Module 3: Managing Datasets

  • Categorizing your data
  • Importing data to Azure machine learning
  • Exploring and transforming data in Azure machine learning
  • Lab : Managing Datasets
    • Prepare Azure SQL database
    • Import data
    • Visualize data
    • Summarize data

Module 4: Preparing Data for use with Azure Machine Learning

  • Data pre-processing
  • Handling incomplete datasets
  • Lab : Preparing data for use with Azure machine learning
    • Explore some data using Power BI
    • Clean the data

Module 5: Using Feature Engineering and Selection

  • Using feature engineering
  • Using feature selection
  • Lab : Using feature engineering and selection
    • Prepare datasets
    • Use Join to Merge data

Module 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
    • Using Azure machine learning studio modules for regression
    • Create and run a neural-network based application

Module 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
    • Using Azure machine learning studio modules for classification.
    • Add k-means section to an experiment
    • Add PCA for anomaly detection.
    • Evaluate the models

Module 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
    • Exploring data using R
    • Analyzing data using Python

Module 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
    • Using hyper-parameters

Module 10: Using Azure Machine Learning Models

  • Deploying and publishing models
  • Consuming Experiments
  • Lab : Using Azure machine learning models
    • Deploy machine learning models
    • Consume a published model

Module 11: Using Cognitive Services

  • Cognitive services overview
  • Processing language
  • Processing images and video
  • Recommending products
  • Lab : Using Cognitive Services
    • Build a language application
    • Build a face detection application
    • Build a recommendation application

Module 12: Using Machine Learning with HDInsight

  • Introduction to HDInsight
  • HDInsight cluster types
  • HDInsight and machine learning models
  • Lab : Machine Learning with HDInsight
    • Provision an HDInsight cluster
    • Use the HDInsight cluster with MapReduce and Spark

Module 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
    • Deploy DSVM
    • Prepare a sample SQL Server database and configure SQL Server and R
    • Use a remote R session
    • Execute R scripts inside T-SQL statements


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