Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Sebastopol, CA : O'Reilly Media
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Windows Azure ; Cloud computing ; Machine learning ; Python (Computer program language) ; Electronic books ; local
    Abstract: Take time to explore Microsoft's Azure machine learning platform, Azure ML-a production environment that simplifies the development and deployment of machine learning models. In this O'Reilly report, Stephen Elston from Quantia Analytics uses a complete data science example (forecasting hourly demand for a bicycle rental system) to show you how to manipulate data, construct models, and evaluate models with Azure ML. The report walks you through key steps in the data science process from problem definition, data understanding, and feature engineering, through construction of a regression model and presentation of results. You'll also learn how to extend Azure ML with Python. Elston uses downloadable Python code and data to demonstrate how to perform data munging, data visualization, and in-depth evaluation of model performance. At the end, you'll learn how to publish your trained models as web services in the Azure cloud. With this report, you'll learn how to: Navigate Azure ML Studio Use the Python Script module Load Python modules from a zip file Use the Sweep Parameters module Apply a SQL transformation Use the Cross Validate Model module Publish a scoring model as a web service to Excel Use Jupyter Notebooks with Azure ML
    Note: Description based on online resource; title from title page (Safari, viewed June 13, 2018)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    [Place of publication not identified] : Infinite Skills
    ISBN: 9781771373845
    Language: English
    Pages: 1 online resource (1 streaming video file (6 hr., 49 min., 14 sec.)) , digital, sound, color
    Keywords: Microsoft Azure SQL Database ; Electronic data processing ; R (Computer program language) ; Machine learning ; Electronic videos ; local
    Abstract: "In this Data Science with Microsoft Azure and R training course, expert author Stephen Elston will teach you how to develop and deploy effective machine learning models in the Microsoft Azure Machine Learning (ML) environment. This course is designed for users that are familiar with R. You will start with an overview of Azure ML, then move into an introduction to R in Azure ML. From there, Stephen will teach you about data munging and SQL in Azure ML, as well as how to use the dplyr package, install R packages in Azure ML, and reshape data with tidyr. This video tutorial also covers feature selection and dimensionality reduction, functional programming with R, and R object communications. Finally, you will learn about Azure ML web services, including how to create and update an Azure ML web service. Once you have completed this computer based training course, you will be fully capable of developing and deploying your own ML models in the Microsoft Azure ML environment."--Resource description page.
    Note: Title from resource description page (viewed July 22, 2015)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Windows Azure ; R (Computer program language) ; Cloud computing ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Take some time to explore Microsoft's Azure machine learning platform, Azure ML-a production environment that simplifies the development and deployment of machine learning models. In this updated and expanded O'Reilly report, Stephen Elston from Quantia Analytics uses a complete data science example (forecasting hourly demand for a bicycle rental system) to show you how to manipulate data, construct models, and evaluate models with Azure ML. The report walks you through key steps in the data science process from problem definition, data understanding, and feature engineering, through construction of a regression model and presentation of results. You'll also learn how to extend Azure ML with R. Elston uses downloadable sample R code and data to demonstrate how to perform data munging, data visualization, and in-depth evaluation of model performance. At the end, you'll learn how to publish your trained models as web services in the Azure cloud. With this 2015 Update, you'll learn how to: Navigate the Azure ML Gallery Use the R Model module Load R packages from a zip file Use the Metadata Editor Publish a scoring model as a web service Use the Cross Validate model module Publish a web service to Excel Apply a SQL transformation Use the new Sweep Parameters module
    Note: Description based on online resource; title from title page (viewed January 4, 2019)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...