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Data Science Using Oracle Data Miner And Oracle R Enterprise Transform Your Business Systems Into An Analytical Powerhouse at Meripustak

Data Science Using Oracle Data Miner And Oracle R Enterprise Transform Your Business Systems Into An Analytical Powerhouse by Das, Apress India

Books from same Author: Das

Books from same Publisher: Apress India

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  • General Information  
    Author(s)Das
    PublisherApress India
    ISBN9781484283516
    Pages289
    BindingSoftcover
    LanguageEnglish
    Publish YearJanuary 2022

    Description

    Apress India Data Science Using Oracle Data Miner And Oracle R Enterprise Transform Your Business Systems Into An Analytical Powerhouse by Das

    Automate the predictive analytics process using Oracle Advanced Analytics. This book talks about how Oracle Data Miner and Oracle R Enterprise which are the two components of Oracle Advanced Analytics can provide a framework for in-database predictive analytics. You'll see a unified architecture and embedded workflow to automate various analytics steps such as data preprocessing, model creation, and storing final model output to tables. You'll take a deep dive into various statistical models commonly used in businesses and how they can be automated for predictive analytics using various SQL, PLSQL, ORE, ODM, and native R packages. You'll get to know various options available in the ODM workflow for driving automation. Also, you'll get an understanding of various ways to integrate ODM packages, ORE, and native R packages using PLSQL for automating the processes. Data Science Using Oracle Data Miner and Oracle R Enterprise starts with an introduction to Data Science, covering why automation is necessary and the level of complexity in various Data Science tasks. Then, it focuses on how predictive analytics can be automated by using Oracle Data Miner and Oracle R Enterprise. Also, it explains when and why ODM and ORE are to be used together for automation.The subsequent chapters detail various statistical processes and machine learning techniques used for predictive analytics such as clustering methods, regression analysis, classification techniques, calculating attribute importance, ensemble models, and neural networks. In these chapters you will also get to understand the automation processes for each of these statistical processes using ODM and ORE along with their application in a real-life business use case. What You Will Learn * Discover the functionality of Oracle Data Miner and Oracle R Enterprise * Gain methods to perform in-database predictive analytics * Use Oracle's SQL and PLSQL APIs for building analytical solutions * Acquire knowledge of common and wide



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