Data Analytics Models and Algorithms for Intelligent Data Analysis /

This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Runkler, Thomas A. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Wiesbaden : Vieweg+Teubner Verlag : Imprint: Vieweg+Teubner Verlag, 2012.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 02612nam a22004455i 4500
001 978-3-8348-2589-6
003 DE-He213
005 20130727044629.0
007 cr nn 008mamaa
008 120928s2012 gw | s |||| 0|eng d
020 |a 9783834825896  |9 978-3-8348-2589-6 
024 7 |a 10.1007/978-3-8348-2589-6  |2 doi 
040 |d GrThAP 
050 4 |a QA76.9.D343 
072 7 |a UNF  |2 bicssc 
072 7 |a UYQE  |2 bicssc 
072 7 |a COM021030  |2 bisacsh 
082 0 4 |a 006.312  |2 23 
100 1 |a Runkler, Thomas A.  |e author. 
245 1 0 |a Data Analytics  |h [electronic resource] :  |b Models and Algorithms for Intelligent Data Analysis /  |c by Thomas A. Runkler. 
264 1 |a Wiesbaden :  |b Vieweg+Teubner Verlag :  |b Imprint: Vieweg+Teubner Verlag,  |c 2012. 
300 |a X, 137 p. 66 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
520 |a This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in numerous courses at the Technical University of Munich, in short courses at several other universities, and in tutorials at scientific conferences. Much of the content is based on the results of industrial research and development projects at Siemens. Content Data Analytics - Data and Relations - Data Preprocessing - Data Visualization - Correlation - Regression - Forecasting - Classification - Clustering Target Groups Students of data analytics for engineering, computer science and math  Practitioners working on data analytics projects The Author Thomas Runkler is doing research at Siemens Corporate Technology in Munich and teaching data analytics and machine learning at the Technical University of Munich. 
650 0 |a Computer science. 
650 0 |a Data structures (Computer science). 
650 0 |a Data mining. 
650 1 4 |a Computer Science. 
650 2 4 |a Data Mining and Knowledge Discovery. 
650 2 4 |a Data Structures. 
650 2 4 |a Computer Science, general. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783834825889 
856 4 0 |u http://dx.doi.org/10.1007/978-3-8348-2589-6  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645)