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Machine Learning for Oracle Database Professionals: Deploying Model-Driven Applications and Automation Pipelines de Heli Helskyaho

Machine Learning for Oracle Database Professionals: Deploying Model-Driven Applications and Automation Pipelines

Autor Heli Helskyaho, Jean Yu, Kai Yu
en Limba Engleză Paperback – 12 iun 2021
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.


What You Will Learn
  • 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


Who This Book Is For

Database developers and administrators who want to learn about machine learning, developers who want to build models and applications using Oracle Database’s built-in machine learning feature set, and administrators tasked with supporting applications on Oracle Database that make use of the Oracle Machine Learning feature set
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Specificații

ISBN-13: 9781484270318
ISBN-10: 1484270312
Pagini: 287
Ilustrații: XVI, 289 p. 156 illus.
Dimensiuni: 178 x 254 mm
Greutate: 0.54 kg
Ediția:1st ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States

Cuprins

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.




Notă biografică

Heli Helskyaho is CEO for Miracle Finland Oy. She holds a master’s degree in computer science from the University of Helsinki and specializes in databases. At the moment she is working on her doctoral studies, researching and teaching at the University of Helsinki. Her research areas cover big data, multi-model databases, schema discovery, and methods and tools for utilizing semi-structured data for decision making. 

Heli has been working in IT since 1990. She has held several positions, but every role has included databases and database designing. She believes that understanding your data makes using the data much easier. She is an Oracle ACE Director, an Oracle Groundbreaker Ambassador, and a frequent speaker at many conferences. She is the author of several books and has been listed as one of the TOP 100 influencers in the IT sector in Finland for each year from 2015 to 2020.

Jean Yu is a Senior Staff MLOps Engineer at Habana Labs, an Intel company. Prior to that, she was a Senior Data Engineer on the IBM Hybrid Cloud Management Data Science Team. Her current interests include deep learning, model productization, and distributed training of massive transformer-based language models. She holds a master's degree in computer science from the University of Texas at San Antonio. She has more than 25 years of experience in developing, deploying, and managing software applications, as well as in leading development teams. Her recent awards include an Outstanding Technical Achievement Award for significant innovation in Cloud Brokerage Cost and Asset Management products in 2019 as well as an Outstanding Technical Achievement Award for Innovation in the Delivery of Remote Maintenance Upgrade for Tivoli Storage Manager in 2011.

Jean is a master inventor with 14 patents granted. She has been a voting member of the IBM Invention Review Board from 2006 to 2020. She has been a speaker at conferences such as North Central Oracle Apps User Group Training Day 2019 and Collaborate 2020.

Kai Yu is a Distinguished Engineer of the Dell Technical Leadership Community. He is responsible for providing technical leadership to Dell Oracle Solutions Engineering.  He has over 27 years of experience in architecting and implementing various IT solutions, specializing in Oracle database, IT infrastructure, and cloud as well as business analytics and machine learning.
Kai has been a frequent speaker at various IT/Oracle conferences with over 200 presentations in more than 20 countries. He also authored 36 articles in technical journals such as IEEE Transactions on Big Data, and has co-authored the Apress book Expert Oracle RAC12c. He has been an Oracle ACE Director since 2010, and has served on the IOUG/Quest Conference committee and served as IOUG RAC SIG president and IOUG CLOUG SIG co-founder and vice president. He received the 2011 OAUG Innovator of Year award and the 2012 Oracle Excellence Award: Technologist of the Year: Cloud Architect by Oracle Magazine. He holds two master’s degrees in computer science and engineering from the Huazhong University of Science and Technology and the University of Wyoming. 

 

Textul de pe ultima copertă

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


Caracteristici

Introduces Oracle Database’s built-in support for machine learning Helps Oracle developers and DBAs make the transition to building machine learning solutions Provides practical examples of machine learning in Oracle Database as well as in Oracle Autonomous Database