Practical synthetic data generation : (Record no. 80382)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01974nam a22002057a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220826b2020 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9788194435013 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.312 El-K |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | El Emam, Khaled |
| 245 ## - TITLE STATEMENT | |
| Title | Practical synthetic data generation : |
| Remainder of title | balancing privacy and the broad availability of data / |
| Statement of responsibility, etc. | Khaled El Emam, Lucy Mosquera and Richard Hoptroff |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | India |
| Name of publisher, distributor, etc. | SPD |
| Date of publication, distribution, etc. | 2020 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 151 p. |
| 365 ## - TRADE PRICE | |
| Price type code | INR |
| Price amount | 675.00. |
| 500 ## - GENERAL NOTE | |
| General note | Building and testing machine learning models requires access to large and diverse data. But where can you find usable datasets without running into privacy issues? This practical book introduces techniques for generating synthetic data—fake data generated from real data—so you can perform secondary analysis to research, understand customer behaviors, develop new products, or generate new revenue.<br/><br/>Data scientists will learn how synthetic data generation provides a way to make such data broadly available for secondary purposes while addressing many privacy concerns. Analysts will learn the principles and steps for generating synthetic data from real datasets. And business leaders will see how synthetic data can help accelerate time to a product or solution.<br/><br/>This book describes:<br/><br/>* Steps for generating synthetic data using multivariate normal distributions<br/>* Methods for distribution fitting covering different goodness-of-fit metrics<br/>* How to replicate the simple structure of the original data<br/>* An approach for modelling data structure to consider complex relationships<br/>* Multiple approaches and metrics you can use to assess data utility<br/>* How analysis performed on real data can be replicated with synthetic data<br/>* Privacy implications of synthetic data and methods to assess identity disclosure |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer simulation |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data mining |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Electronic data processing |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Acquisition of data sets |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data protection |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | 003-007 | BITS Pilani Hyderabad | BITS Pilani Hyderabad | General Stack (For lending) | 26/08/2022 | 006.312 El-K | 46030 | 13/11/2024 | 26/08/2022 | Books |