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lgli/Peter Ghavami - Big Data Analytics Methods (2019, ).epub
BIG DATA ANALYTICS METHODS : analytics techniques in data mining, deep learning and natural ... language processing 🔍
Peter Ghavami; Walter de Gruyter Inc Walter de Gruyter Inc, De Gruyter, Berlin, 2019
英语 [en] · EPUB · 6.3MB · 2019 · 📘 非小说类图书 · 🚀/lgli/zlib · Save
描述
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.
备用文件名
zlib/no-category/Peter Ghavami/Big Data Analytics Methods_5445322.epub
备选作者
Peter K Ghavami
备选作者
Ghavami, Peter
备用出版商
DEG Press
备用出版商
DE G PR
备用版本
Business et economics, 2nd edition, Boston ; Berlin, 2020
备用版本
Place of publication not identified, 2019
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United States, United States of America
备用版本
2nd Edition, Berlin, 2019
备用版本
2nd edition, Boston, 2019
备用版本
1, 20191216
备用版本
2, PT, 2019
备用版本
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备用描述
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. 0 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
备用描述
Keine Beschreibung vorhanden.
Erscheinungsdatum: 16.12.2019
开源日期
2020-04-12
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