Big Data Analytics Methods

Peter Ghavami

ISBN 10: 1547417951 / ISBN 13: 9781547417957

Edité par Boston Dez 2019, 2019

A propos de cet article

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.

N° de réf. du vendeur 9781547417957

Détails bibliographiques

• Titre: Big Data Analytics Methods
• Éditeur: Boston Dez 2019
• Date de parution: 2019
• Langue: anglais
• ISBN à 10 chiffres: 1547417951
• ISBN à 13 chiffres: 9781547417957
• Reliure: Taschenbuch
• Édition: 2ème Édition
• État de l'article: Neu

A propos de ce titre

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.

À propos de l?auteur

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