• Presencial

Perform Cloud Data Science with Azure Machine Learning (20774)


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.

Destinatários

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.

Pré-requisitos

  • 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.

Objetivos

  • 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

Programa

  • Introduction to Machine
  • Introduction to Azure Machine
  • Managing Datasets
  • Preparing Data for use with Azure Machine Learning
  • Using Feature Engineering and Selection
  • Building Azure Machine Learning Models
  • Using Classification and Clustering with Azure machine learning models
  • Using R and Python with Azure Machine Learning
  • Initializing and Optimizing Machine Learning Models
  • Using Azure Machine Learning Models
  • Using Cognitive Services
  • Using Machine Learning with HDInsight
  • Using R Services with Machine Learning

Introduction to Machine 

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

Introduction to Azure Machine 

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

Managing Datasets

  • 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

  • Data pre-processing
  • Handling incomplete datasets

Using Feature Engineering and Selection

  • Using feature engineering
  • Using feature selection

Building Azure Machine Learning Models

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

Using Classification and Clustering with Azure machine learning models

  • Using classification algorithms
  • Clustering techniques
  • Selecting algorithms

Using R and Python with Azure Machine Learning

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

Initializing and Optimizing Machine Learning Models

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

Using Azure Machine Learning Models

  • Deploying and publishing models
  • Consuming Experiments

Using Cognitive Services

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

Using Machine Learning with HDInsight

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

Using R Services with Machine Learning

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

Inscreva-se

Dados Pessoais

Dados para faturação

   Os seus dados pessoais são recolhidos em conformidade com o Regulamento Geral de Proteção de Dados (RGPD).Consente que os seus dados sejam utilizados, nos termos da nossa Politica de Privacidade, para o contacto/envio de:

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Para mais informações, consulte a Política de Privacidade do Grupo Rumos. Pode retirar o seu consentimento a qualquer momento, através do botão “Cancelar subscrição” ou “Unsubscribe” que estão presentes em cada comunicação enviada, bem como exercer os direitos descritos na política de privacidade

Perform Cloud Data Science with Azure Machine Learning (20774)

  • Datas
    04 Fev a 08 Fev 2019
    Porto
  • Horário
    Laboral
    das 09h30 às 17h30
  • Nº Horas
    35
  • Preço
    1740€

Perform Cloud Data Science with Azure Machine Learning (20774)

Área

Dados

Como chegou até nós

Os seus dados pessoais são recolhidos em conformidade com o Regulamento Geral de Proteção de Dados (RGPD).

Consente que os seus dados sejam utilizados, nos termos da nossa Politica de Privacidade, para o contacto/envio de:

Ações de informação, de marketing de produtos e serviços, como campanhas e eventos?

Para mais informações, consulte a Política de Privacidade do Grupo Rumos.
pode retirar o seu consentimento a qualquer momento através do botão Cancelar subscrição ou Unsubscribe que estão presentes em cada comunicação enviada, bem como exercer os direitos descritos na politica de privacidade