| 000 | 00000nam u2200205 a 4500 | |
| 001 | 000046026905 | |
| 005 | 20200513120216 | |
| 006 | m d | |
| 007 | cr | |
| 008 | 200508s2016 sz a ob 000 0 eng d | |
| 020 | ▼a 9783319292069 | |
| 040 | ▼a 211009 ▼c 211009 ▼d 211009 | |
| 082 | 0 4 | ▼a 001.4/2 ▼2 23 |
| 084 | ▼a 001.42 ▼2 DDCK | |
| 090 | ▼a 001.42 | |
| 100 | 1 | ▼a Akerkar, Rajendra. |
| 245 | 1 0 | ▼a Intelligent techniques for data science ▼h [electronic resource] / ▼c by Rajendra Akerkar, Priti Srinivas Sajja. |
| 260 | ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2016. | |
| 300 | ▼a 1 online resource (xvi, 272 p.) : ▼b ill. (some col.). | |
| 500 | ▼a Title from e-Book title page. | |
| 504 | ▼a Includes bibliographical references. | |
| 505 | 0 | ▼a Preface -- Introduction -- Data Analytics -- Basic Learning Algorithms -- Fuzzy Logic -- Artificial Neural Networks -- Genetic Algorithms and Evolutionary Computing -- Other Metaheuristics and Classification Approaches -- Analytics and Big Data -- Data Analytics Using R -- Appendix I: Tools for Data Science -- Appendix II: Tools for Computational Intelligence. |
| 520 | ▼a 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. | |
| 530 | ▼a Issued also as a book. | |
| 538 | ▼a Mode of access: World Wide Web. | |
| 650 | 0 | ▼a Quantitative research. |
| 650 | 0 | ▼a Data mining. |
| 650 | 0 | ▼a Big data. |
| 700 | 1 | ▼a Sajja, Priti Srinivas. |
| 856 | 4 0 | ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-29206-9 |
| 945 | ▼a KLPA | |
| 991 | ▼a E-Book(소장) |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 중앙도서관/e-Book 컬렉션/ | 청구기호 CR 001.42 | 등록번호 E14021543 | 도서상태 대출불가(열람가능) | 반납예정일 | 예약 | 서비스 |