Predictive analytics for dummies (Record no. 32582)
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| LIBRARY OF CONGRESS CONTROL NUMBER | |
|---|---|
| LC control number | 2016951998 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781119267003 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1119267005 |
| DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Call number | 658.403802856312 BA PR |
| MAIN ENTRY--PERSONAL NAME | |
| Authors | Bari, Anasse |
| TITLE STATEMENT | |
| Title | Predictive analytics for dummies |
| Statement of responsibility, etc | by Anasse Bari, Ph.D., Mohamed Chaouchi, and Tommy Jung |
| EDITION STATEMENT | |
| Edition | 2nd ed. |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Hoboken, New York : |
| Publisher | John Wiley and Sons, |
| Date | c2017. |
| PHYSICAL DESCRIPTION | |
| Extent | viii, 443 p. : |
| Other Details | ill. ; |
| Size | 24 cm. |
| SERIES STATEMENT | |
| Series statement | --For dummies |
| GENERAL NOTE | |
| General note | Includes index. |
| CONTENTS | |
| Contents | Introduction. -- pt. 1. Getting started with predictive analytics. Entering the arena; Predictive analytics in the wild; Exploring your data types and associated techniques; Complexities of data -- pt. 2. Incorporating algorithms in your models. Applying models; Identifying similarities in data; Predicting the future using data classification -- pt. 3. Developing a roadmap. Convincing your management to adopt predictive analytics ; Preparing data ; Building a predictive model ; Visualization of analytical results -- pt. 4. Programming predictive analytics. Creating basic prediction examples ; Creating basic examples of unsupervised predictions ; Predictive modeling with R ; Avoiding analysis traps ; -- pt. 5. Targeting big data Getting ready for enterprise analytics pt. 6 The part of tens. Ten reasons to implement predictive analytics ; Ten steps to build a predictive analytic model. |
| SUMMARY | |
| Summary | Business today relies on effectively using data to predict trends and sales. Predictive analytics is the tool that can make it happen, and this book eliminates the tricks and shows you how to use it. You'll learn to prepare and process your data, create goals, build a predictive model, get your organization's stakeholders on board and more. |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Management |
| Geographic | Data processing |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Management |
| Geographic | Mathematical models |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Data mining |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Management |
| Geographic | Data processing |
| ADDED ENTRY | |
| Name | Chaouchi, Mohamed |
| ADDED ENTRY | |
| Name | Jung, Tommy |
| SERIES UNIFORM TITLE | |
| Series Uniform Title | For dummies |
| MAIN ENTRY--PERSONAL NAME | |
| -- | 10606 |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| -- | 5432 |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| -- | 10607 |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| -- | 312 |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| -- | 5432 |
| ADDED ENTRY | |
| -- | 10609 |
| ADDED ENTRY | |
| -- | 10610 |
| SERIES UNIFORM TITLE | |
| -- | 10611 |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent location | Current location | Shelving location | Date acquired | Source of acquisition | Total Checkouts | Full call number | Barcode | Date last seen | Date last borrowed | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| University of Wollongong in Dubai | University of Wollongong in Dubai | Main Collection | 2017-10-31 | AMAUK | 2 | 658.403802856312 BA PR | T0057959 | 2020-06-08 | 2019-04-09 | 2017-10-25 | REGULAR |