Mastering material for dealing with DBA certification exams
Key Features
Book Description
IBM Db2 is a relational database management system (RDBMS) that helps you store, analyze, and retrieve data efficiently. This comprehensive book is designed to help you master all aspects of IBM Db2 database administration and prepare you to take and
pass IBM's Certification Exams C2090-600. Building on years of extensive experience,
the authors take you through all areas covered by the test. The book delves deep into each certification topic: Db2 server management, physical design, business rules implementation, activity monitoring, utilities, high availability, and security. IBM Db2 11.1 Certification Guide provides you with more than 150 practice questions and answers, simulating real certification examination questions. Each chapter includes an extensive set of practice questions along with carefully explained answers.
This book will not just prepare you for the C2090-600 exam but also help you troubleshoot day-to-day database administration challenges.
What you will learn
Who this book is for
The IBM Db2 11.1 Certification Guide is an excellent choice for database administrators, architects, and application developers who are keen to obtain certification in Db2. Basic understanding of Db2 is expected in order to get the most out of this guide.Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Mohankumar Saraswatipura is a database solutions architect focusing on IBM Db2, Linux, Unix, Windows, and SAP HANA solutions. He is an IBM Champion (2010-2018) and a DB2's Got Talent 2013 winner. He is also a frequent speaker at the DB2Night Show and IDUG North America conferences. He has written dozens of technical papers for IBM developerWorks, Data Magazine, and the DB2 10.1/10.5 certification guide. He holds a Master's of technology in computer science and an executive MBA from IIM Calcutta.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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Zustand: New. Idioma/Language: Inglés. Create scalable machine learning applications to power a modern data-driven business using Spark 2. xAbout This Book* Get to the grips with the latest version of Apache Spark* Utilize Spark's machine learning library to implement predictive analytics* Leverage Spark's powerful tools to load, analyze, clean, and transform your dataWho This Book Is ForIf you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages. What You Will Learn* Get hands-on with the latest version of Spark ML* Create your first Spark program with Scala and Python* Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2* Access public machine learning datasets and use Spark to load, process, clean, and transform data* Use Spark's machine learning library to implement programs by utilizing well-known machine learning models* Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models* Write Spark functions to evaluate the performance of your machine learning modelsIn DetailThis book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business. Style and approachThis practical tutorial with real-world use cases enables you to develop your own machine learning systems with Spark. The examples will help you combine various techniques and models into an intelligent machine learning system. *** Nota: Los envíos a España peninsular, Baleares y Canarias se realizan a través de mensajería urgente. No aceptamos pedidos con destino a Ceuta y Melilla. Bestandsnummer des Verkäufers 17334939
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