- Format
- Häftad (Paperback / softback)
- Språk
- Engelska
- Antal sidor
- 769
- Utgivningsdatum
- 2017-09-16
- Upplaga
- 1st ed. 2017
- Förlag
- Springer Verlag, Singapore
- Medarbetare
- Lu, Zeguang (red.)
- Illustratör/Fotograf
- Bibliographie
- Illustrationer
- 351 Illustrations, black and white; XXV, 769 p. 351 illus.
- Dimensioner
- 234 x 156 x 40 mm
- Vikt
- Antal komponenter
- 1
- Komponenter
- 1 Paperback / softback
- ISBN
- 9789811063848
- 1094 g
Du kanske gillar
-
Data Science
Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22-24, 2017, Proceedings, Part I
1553- Skickas inom 7-10 vardagar.
- Gratis frakt inom Sverige över 199 kr för privatpersoner.
Finns även somPassar bra ihop
De som köpt den här boken har ofta också köpt Broadband Communications, Networks, and Systems av Qingshan Li, Shengli Song, Rui Li, Yueshen Xu, Wei Xi (häftad).
Köp båda 2 för 2333 krKundrecensioner
Har du läst boken? Sätt ditt betyg »Fler böcker av författarna
-
NMDA Receptor Protocols
Min Li
-
Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics
Min Li, Jianxin Wang, Yi Pan
-
Aesthetic Surgery of the Craniofacial Skeleton
J G McCarthy, Min Li, F O Monasterio, John J Iii Coleman, B L Eppley
Innehållsförteckning
Mathematical Issues in Data Science.- Computational Theory for Data Science, Big Data Management and Applications.- Data Quality and Data Preparation.- Evaluation and Measurement in Data Science.- Data Visualization.- Big Data Mining and Knowledge Management.- Infrastructure for Data Science.- Machine Learning for Data Science.- Data Security and Privacy.- Applications of Data Science.- Case Study of Data Science.- Multimedia Data Management and Analysis.- Data-driven Scientific Research.- Data-driven Bioinformatics.- Data-driven Healthcare.- Data-driven Management.- Data-driven eGovernment.- Data-driven Smart City/Planet.- Data Marketing and Economics.- Social Media and Recommendation Systems.- Data-driven Security.- Data-driven Business Model Innovation.- Social and/or organizational impacts of Data Science.