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./p> 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 real¿world 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.
| Autorius: | Priti Srinivas Sajja, Rajendra Akerkar, |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2016 |
| Knygos puslapių skaičius: | 288 |
| ISBN-10: | 3319292056 |
| ISBN-13: | 9783319292052 |
| Formatas: | 241 x 160 x 22 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
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