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Machine learning for Oracle database...

Helskyaho, Heli.

Machine learning for Oracle database professionalsdeploying model-driven applications and automation pipelines /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning for Oracle database professionalsby Heli Helskyaho, Jean Yu, Kai Yu.
Reminder of title:	deploying model-driven applications and automation pipelines /
Author:	Helskyaho, Heli.
other author:	Yu, Jean.
Published:	Berkeley, CA :Apress :2021.
Description:	xvi, 289 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Machine learning.
Online resource:	https://doi.org/10.1007/978-1-4842-7032-5
ISBN:	9781484270325$q(electronic bk.)

Machine learning for Oracle database professionalsdeploying model-driven applications and automation pipelines /
Helskyaho, Heli.

Machine learning for Oracle database professionalsdeploying model-driven applications and automation pipelines /[electronic resource] :by Heli Helskyaho, Jean Yu, Kai Yu. - Berkeley, CA :Apress :2021. - xvi, 289 p. :ill., digital ;24 cm.

1. Introduction to Machine Learning -- 2. Oracle and Machine Learning -- 3: Oracle Machine Learning for SQL -- 4. Oracle Autonomous Database for Machine Learning -- 5. Running Oracle Machine Learning with Autonomous Database -- 6. Building Machine Learning Models with OML Notebooks -- 7. Oracle Analytics Cloud -- 8. Delivery and Automation Pipeline in Machine Learning -- 9. ML Deployment Pipeline Using Oracle Machine Learning -- 10. Building Reproducible ML Pipelines Using Oracle Machine Learning.

Database developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle's Autonomous Database cloud offering. The book covers the technologies that make up the Oracle Machine Learning (OML) platform, including OML4SQL, OML Notebooks, OML4R, and OML4Py. The book focuses on Oracle Machine Learning as part of the Oracle Autonomous Database collaborative environment. Also covered are advanced topics such as delivery and automation pipelines. Throughout the book you will find practical details and hand-on examples showing you how to implement machine learning and automate deployment of machine learning. Discussion around the examples helps you gain a conceptual understanding of machine learning. Important concepts discussed include the methods involved, the algorithms to choose from, and mechanisms for process and deployment. Seasoned database professionals looking to make the leap into machine learning as a growth path will find much to like in this book as it helps you step up and use your current knowledge of Oracle Database to transition into providing machine learning solutions. You will: Use the Oracle Machine Learning (OML) Notebooks for data visualization and machine learning model building and evaluation Understand Oracle offerings for machine learning Develop machine learning with Oracle database using the built-in machine learning packages Develop and deploy machine learning models using OML4SQL and OML4R Leverage the Oracle Autonomous Database and its collaborative environment for Oracle Machine Learning Develop and deploy machine learning projects in Oracle Autonomous Database Build an automated pipeline that can detect and handle changes in data/model performance.

ISBN: 9781484270325$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-7032-5doiSubjects--Uniform Titles:

Oracle (Computer file)
Subjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5 / .H45 2021

Dewey Class. No.: 006.31

Machine learning for Oracle database professionalsdeploying model-driven applications and automation pipelines /
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505 0 $a 1. Introduction to Machine Learning -- 2. Oracle and Machine Learning -- 3: Oracle Machine Learning for SQL -- 4. Oracle Autonomous Database for Machine Learning -- 5. Running Oracle Machine Learning with Autonomous Database -- 6. Building Machine Learning Models with OML Notebooks -- 7. Oracle Analytics Cloud -- 8. Delivery and Automation Pipeline in Machine Learning -- 9. ML Deployment Pipeline Using Oracle Machine Learning -- 10. Building Reproducible ML Pipelines Using Oracle Machine Learning.
520 $a Database developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle's Autonomous Database cloud offering. The book covers the technologies that make up the Oracle Machine Learning (OML) platform, including OML4SQL, OML Notebooks, OML4R, and OML4Py. The book focuses on Oracle Machine Learning as part of the Oracle Autonomous Database collaborative environment. Also covered are advanced topics such as delivery and automation pipelines. Throughout the book you will find practical details and hand-on examples showing you how to implement machine learning and automate deployment of machine learning. Discussion around the examples helps you gain a conceptual understanding of machine learning. Important concepts discussed include the methods involved, the algorithms to choose from, and mechanisms for process and deployment. Seasoned database professionals looking to make the leap into machine learning as a growth path will find much to like in this book as it helps you step up and use your current knowledge of Oracle Database to transition into providing machine learning solutions. You will: Use the Oracle Machine Learning (OML) Notebooks for data visualization and machine learning model building and evaluation Understand Oracle offerings for machine learning Develop machine learning with Oracle database using the built-in machine learning packages Develop and deploy machine learning models using OML4SQL and OML4R Leverage the Oracle Autonomous Database and its collaborative environment for Oracle Machine Learning Develop and deploy machine learning projects in Oracle Autonomous Database Build an automated pipeline that can detect and handle changes in data/model performance.
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