Intelligent techniques for data science / Rajendra Akerkar and Priti Srinivas Sajja.
Material type:
- 9783319292052
- 006.312 23 Ak314
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
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Books | ISI Library, Kolkata | 006.312 Ak314 (Browse shelf(Opens below)) | Available | 138343 |
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006.312 Ah285 Practical guide to data mining for business and industry / | 006.312 Ah285 Practical guide to data mining for business and industry / | 006.312 Ak314 Big data computing / | 006.312 Ak314 Intelligent techniques for data science / | 006.312 An549 Visual data mining : | 006.312 B213 Text mining with MATLAB / | 006.312 B534 Text mining |
1. Introduction to data science --
2. Data Analytics --
3. Basic Learning Algorithms --
4. Fuzzy Logic --
5. Artificial Neural Networks --
6. Genetic Algorithms and Evolutionary Computing --
7. Other Metaheuristics and Classification Approaches --
8. Analytics and Big Data --
9. Data Analytics Using R --
Appendix I: Tools for Data Science --
Appendix II: Tools for Computational Intelligence.
This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions. The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.
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