Data science, analytics and machine learning with R / (Record no. 749901)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01771cam a22002177i 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 012824271X |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780128242711 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 658.05631 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Fávero, Luiz Paulo |
| 245 10 - TITLE STATEMENT | |
| Title | Data science, analytics and machine learning with R / |
| Statement of responsibility, etc | Luiz Paulo Fávero, Patrícia Belfiore [and] Rafael de Freitas Souza. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | London : |
| Name of publisher | Academic Press, |
| Year of publication | c.2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xii, 648p. ; |
| Other physical details | ill. : |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes bibliographic references (p. 639-640) and index. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear. -- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Business |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | R (Computer program language) |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Belfiore, Patrícia Prado |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | De Freitas Souza, Rafael |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Reference |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home Library | Current Location | Date acquired | Full call number | Accession Number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Dept. of Computer Science | Dept. of Computer Science | 21/06/2025 | 658.05631 FAV/D | DCS5216 | 21/06/2025 | Reference |
