MOC 20774

PERFORM CLOUD DATA SCIENCE WITH AZURE MACHINE LEARNING

 

Duración:
25 horas lectivas.
5 Horas / Día

Inicio » MOC 20774

Detalles

 

Requisitos previos MOC 20774:

In addition to their professional experience, students who 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.

 

Ubicación

  • Presencial en Madrid y Barcelona
  • En oficina de cliente
  • Online Direct

 

Objetivos MOC 20774

El propósito principal del curso es brindar a los estudiantes la capacidad de analizar y presentar datos mediante el aprendizaje automático de Azure y proporcionar una introducción al uso del aprendizaje automático con herramientas de big data como HDInsight y R Services.

Temario MOC 20774

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

 

Module 2: Introduction to Azure Machine

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

Lab : Introduction to Azure machine learning

 

Module 3: Managing Datasets

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

Lab : Managing Datasets

 

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

 

Module 5: Using Feature Engineering and Selection

  • Using feature engineering
  • Using feature selection

Lab : Using feature engineering and selection

 

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

 

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

 

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

 

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

 

Module 10: Using Azure Machine Learning Models

  • Deploying and publishing models
  • Consuming Experiments

Lab : Using Azure machine learning models

 

Module 11: Using Cognitive Services

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

Lab : Using Cognitive Services

 

Module 12: Using Machine Learning with HDInsight

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

Lab : Machine Learning with HDInsight

 

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


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