Data Mining Finance

Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner, 3rd Edition

Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner by Galit Shmueli, Peter C. Bruce, Nitin R. Patel
2016 | ISBN: 1118729277 | English | 552 pages | PDF | 156 MB
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro

Galit Shmueli, Peter C. Bruce, "Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro"
2016 | ISBN-10: 1118877438 | 464 pages | PDF | 128 MB

Advances in Data Mining: Applications and Theoretical Aspects (Repost)  eBooks & eLearning

Posted by melia at Feb. 4, 2015
Advances in Data Mining: Applications and Theoretical Aspects (Repost)

Petra Perner, "Advances in Data Mining: Applications and Theoretical Aspects"
English | 2010 | ISBN: 3642143997 | 654 pages | PDF | 14.82 MB

Applications of Data Mining in E-Business and Finance by Z.-H. Zhou [Repost]  eBooks & eLearning

Posted by tanas.olesya at Jan. 22, 2015
Applications of Data Mining in E-Business and Finance by Z.-H. Zhou [Repost]

Applications of Data Mining in E-Business and Finance (Frontiers in Artificial Intelligence and Applications) by Z.-H. Zhou
English | Aug 15, 2008 | ISBN: 1586038907 | 157 Pages | PDF | 4 MB

The application of Data Mining (DM) technologies has shown an explosive growth in an increasing number of different areas of business, government and science.

Data Mining in Finance: Advances in Relational and Hybrid Methods [Repost]  eBooks & eLearning

Posted by ChrisRedfield at Sept. 8, 2013
Data Mining in Finance: Advances in Relational and Hybrid Methods [Repost]

Boris Kovalerchuk, ‎Evgenii Vityaev - Data Mining in Finance: Advances in Relational and Hybrid Methods
Published: 2000-03-01 | ISBN: 0792378040 | PDF | 328 pages | 21 MB

Applications of Data Mining in E-Business and Finance [Repost]  eBooks & eLearning

Posted by ChrisRedfield at July 30, 2013
Applications of Data Mining in E-Business and Finance [Repost]

Carlos Soares, Yonghong Peng, Jun Meng, Takashi Washio, Zhi-Hua Zhou - Applications of Data Mining in E-Business and Finance
Published: 2008-08-15 | ISBN: 1586038907 | PDF | 120 pages | 4 MB

Principles of Data Mining (Undergraduate Topics in Computer Science) [Repost]  eBooks & eLearning

Posted by hill0 at Feb. 20, 2017
Principles of Data Mining (Undergraduate Topics in Computer Science) [Repost]

Principles of Data Mining (Undergraduate Topics in Computer Science) by Max Bramer
English | 17 Nov. 2016 | ISBN: 1447173066 | 544 Pages | PDF | 4.23 MB

This book explains the principal techniques of data mining, for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed examples, with a focus on algorithms rather than mathematical formalism.

Data Mining with R: Go from Beginner to Advanced  eBooks & eLearning

Posted by naag at Feb. 19, 2017
Data Mining with R: Go from Beginner to Advanced

Data Mining with R: Go from Beginner to Advanced
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 12 Hours | Lec: 80 | 3.79 GB
Genre: eLearning | Language: English

Learn to use R software for data analysis, visualization, and to perform dozens of popular data mining techniques.
Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading

Kevin Davey, "Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading (Wiley Trading)"
ISBN: 1118778987 | 2014 | EPUB | 288 pages | 4 MB

Classification and Data Mining (Repost)  eBooks & eLearning

Posted by AvaxGenius at Feb. 17, 2017
Classification and Data Mining (Repost)

Classification and Data Mining By Antonio Giusti, Gunter Ritter, Maurizio Vichi
English | PDF | 2013 | 291 Pages | ISBN : 3642288936 | 6.17 MB

​​​​​​​​​This volume contains both methodological papers showing new original methods, and papers on applications illustrating how new domain-specific knowledge can be made available from data by clever use of data analysis methods.