Big Data Analytics Methods

Peter Ghavami

ISBN 10: 1547417951 / ISBN 13: 9781547417957

Published by De Gruyter Dez 2019, 2019

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.deGruyter Boston, Genthiner Straße 13, 10785 Berlin 254 pp. Englisch.

Seller Inventory # 9781547417957

Bibliographic Details

• Title: Big Data Analytics Methods
• Publisher: De Gruyter Dez 2019
• Publication Date: 2019
• Language: English
• ISBN 10: 1547417951
• ISBN 13: 9781547417957
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 240W x 170H x 14D millimeters 240 millimeters width by 170 millimeters height by 14 millimeters depth
• Weight: 438 grams

About this title

Synopsis

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.

About the Author

Peter Ghavami, Senior Vice President, Head of Wholesale Data Science & Analytics at Bank of America, USA