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: 300
Pages: 300
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: 1150
Pages: 1150
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: 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: 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: 432
Pages: 432
The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to
Language: en
Pages: 316
Pages: 316
When measuring a few factors on a complex test unit, it is frequently important to break down the factors all the while, as opposed to separate them and think o
Language: en
Pages: 253
Pages: 253
Master the Big Data Capabilities of Oracle R Enterprise Effectively manage your enterprise’s big data and keep complex processes running smoothly using the ha
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: 399
Pages: 399
The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research direct
