Dauer: 5 Tage / Kurssprache: Deutsch
Das Kursziel ist es, den Studenten die Fähigkeit zu vermitteln, Daten mit Hilfe von Azure Machine Learning zu analysieren und darzustellen, und eine Einführung in die Verwendung von Machine Learning mit großen Datenwerkzeugen wie HDInsight und R Services zu geben.
Course OutlineModule 1: Introduction to Machine Learning
Module 2: Introduction to Azure Machine Learning
Module 3: Managing Datasets
Module 4: Preparing Data for use with Azure Machine Learning
Module 5: Using Feature Engineering and Selection
Module 6: Building Azure Machine Learning Models
Module 7: Using Classification and Clustering with Azure machine learning models
Module 8: Using R and Python with Azure Machine Learning
Module 9: Initializing and Optimizing Machine Learning Models
Module 10: Using Azure Machine Learning Models
Module 11: Using Cognitive Services
Module 12: Using Machine Learning with HDInsight
Module 13: Using R Services with Machine Learningweniger anzeigen
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
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.
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