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

"Asian American Studies Now" truly represents the enormous changes occurring in Asian American communities and the world, changes that require a reconsideration of how the interdisciplinary field of Asian American studies is defined and taught. This comprehensive anthology, arranged in four parts and featuring a stellar group of contributors, summarizes and defines the current shape of this rapidly changing field, addressing topics such as transnationalism, U.S. imperialism, multiracial identity, racism, immigration, citizenship, social justice, and pedagogy.

Jean Yu-wen Shen Wu and Thomas C. Chen have selected essays for the significance of their contribution to the field and their clarity, brevity, and accessibility to readers with little to no prior knowledge of Asian American studies. Featuring both reprints of seminal articles and groundbreaking texts, as well as bold new scholarship, "Asian American Studies Now" addresses the new circumstances, new communities, and new concerns that are reconstituting Asian America.