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

ISBN-13: 9781484270318 / Angielski / Miękka / 2021 / 289 str.

Heli Helskyaho; Jean Yu; Kai Yu

Opis

Intermediate-Advanced user level

Spis treści

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

O autorze

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.

Blurb

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