Predictive Analytics Using Oracle Data Miner
| Author | : Brendan Tierney |
| Publisher | : McGraw Hill Professional |
| Total Pages | : 464 |
| Release | : 2014-08-08 |
| ISBN 10 | : 9780071821759 |
| ISBN 13 | : 0071821759 |
| Language | : EN, FR, DE, ES & NL |
Language: en
Pages: 464
Pages: 464
Build Next-Generation In-Database Predictive Analytics Applications with Oracle Data Miner “If you have an Oracle Database and want to leverage that data to d
Language: en
Pages: 289
Pages: 289
Automate the predictive analytics process using Oracle Data Miner and Oracle R Enterprise. This book talks about how both these technologies can provide a frame
Language: en
Pages: 1200
Pages: 1200
For Oracle tuning professionals wishing to add more tools to their Oracle tuning toolbox, this guidebook introduces the various tuning analytical tools and help
Language: en
Pages: 541
Pages: 541
This book offers a unique blend of reports on both theoretical models and their applications in the area of Intelligent Information and Database Systems. The re
Language: en
Pages: 446
Pages: 446
Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately
Language: en
Pages: 346
Pages: 346
Most of the high-profile cases of real or perceived unethical activity in data science aren’t matters of bad intent. Rather, they occur because the ethics sim
Language: en
Pages: 3994
Pages: 3994
Includes articles in topic areas such as autonomic computing, operating system architectures, and open source software technologies and applications.
Language: en
Pages: 530
Pages: 530
"This book presents quality articles focused on key issues concerning the management and utilization of information technology"--Provided by publisher.
Language: en
Pages: 470
Pages: 470
"This book presents current research in Knowledge Management, highlighting new technologies, approaches, issues, solutions, or cases that can help an organizati
Language: en
Pages: 1383
Pages: 1383
Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and
