Big data analytics methods : (Record no. 37509)
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| LIBRARY OF CONGRESS CONTROL NUMBER | |
|---|---|
| LC control number | 2019950180 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781547417957 |
| DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Call number | 006.312 GH BI |
| MAIN ENTRY--PERSONAL NAME | |
| Authors | Ghavami, Peter |
| TITLE STATEMENT | |
| Title | Big data analytics methods : |
| Subtitle | analytics techniques in data mining, deep learning and natural language processing |
| Statement of responsibility, etc | Peter Ghavami |
| EDITION STATEMENT | |
| Edition | 2nd ed. |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Boston : |
| Publisher | De Gruyter Inc., |
| Date | c2020. |
| PHYSICAL DESCRIPTION | |
| Extent | xv, 237 p. : |
| Other Details | ill. ; |
| Size | 25 cm. |
| CONTENTS | |
| Contents | • Frontmatter • Acknowledgments • About the Author • Contents • Introduction • Part I: Big Data Analytics • Chapter 1. Data Analytics Overview • Chapter 2. Basic Data Analysis • Chapter 3. Data Analytics Process • Part II: Advanced Analytics Methods • Chapter 4. Natural Language Processing • Chapter 5. Quantitative Analysis—Prediction and Prognostics • Chapter 6. Advanced Analytics and Predictive Modeling • Chapter 7. Ensemble of Models: Data Analytics Prediction Framework • Chapter 8. Machine Learning, Deep Learning—Artificial Neural Networks • Chapter 9. Model Accuracy and Optimization • Part III: Case Study—Prediction and Advanced Analytics in Practice • Chapter 10. Ensemble of Models—Medical Prediction Case Study: Data Types, Data Requirements and Data Pre-Processing • Appendices • References • Index. |
| SUMMARY | |
| Summary | Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics. |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Big data |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Data analysis |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Data mining |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Machine learning |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | Neural networks |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Heading | BUSINESS & ECONOMICS / Information Management |
| ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://uowd.box.com/s/5tfcyofz1iagzl63whqgic1sfxmdzuij |
| Public note | Location Map |
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| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent location | Current location | Shelving location | Date acquired | Source of acquisition | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Public note |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| University of Wollongong in Dubai | University of Wollongong in Dubai | Main Collection | 2020-03-18 | Friendship bookshop | 006.312 GH BI | T0064374 | 2020-02-11 | 2020-02-11 | REGULAR | Mar2020 |