Big Data Analytics Methods
Language: English
Published by De Gruyter, US, 2019
- Softcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
£ 56.86
Quantity: 2 available
Add to basketItem description from seller
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.…
Seller Inventory # LU-9781547417957
- Title
- Big Data Analytics Methods
- Author
- Peter Ghavami
- Publisher
- De Gruyter, US
- Publication year
- 2019
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1547417951
- ISBN 13
- 9781547417957
- Edition
- 2nd Edition.
- Item weight
- 490 grams
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
Rarewaves.com USA
London, London, United Kingdom
AbeBooks seller since June 11, 2025
Shipping rates from United Kingdom to U.S.A.
| Item | 7 to 12 business days | 7 to 12 business days |
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