Big Data Analytics Methods - Analytics Techniques in Data Mining, Deep Learning and Natural Language Processing

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.

Sommario

Introduction
PART I: Big Data Analytics
Chapter 1. Data Analytics Overview
Chapter 2. Basic Data Analysis
Chapter 3. Data Visualization Tools
PART II: Advanced Analytics Methods
Chapter 4. Natural Language Processing
Chapter 5. Quantitative Analysis - Prediction and Prognostics
Chapter 6. Advanced Analytics & Predictive Modeling
Chapter 7. Ensemble of Models
Chapter 8. Machine Learning, Deep Learning - Artificial Neural Networks
Chapter 9. Model Accuracy & Optimization
PART III: Case Study - Prediction & Advanced Analytics in Practice
Chapter 10: Ensemble of Models - Medical Prediction Case Study
Appendix A: Prognostics Methods
Appendix B: A Neural Network Example
Appendix C: Back Propagation Algorithm Derivation
Appendix D: NeuroSolutions Software Description
Appendix E: The Oracle Program
References

Info autore

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

Dettagli sul prodotto

• Autori: Peter Ghavami
• Editore: De Gruyter
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 02.09.2019
• EAN: 9781547417957
• ISBN: 978-1-5474-1795-7
• Pagine: 238
• Dimensioni: 171 mm x 240 mm x 20 mm
• Peso: 438 g
• Illustrazioni: 88 b/w ill., 14 b/w tbl.
• Categorie: Saggistica > Politica, società, economia > Economia aziendale, impresa; Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica; Scienze sociali, diritto, economia > Economia > Economia aziendale; Management, Rechnungswesen, Wissensmanagement, Datenbank, Informatik, Finanz- und Rechnungswesen, Data Mining, BUSINESS & ECONOMICS / Information Management, Management / Wissensmanagement, Knowledge Management, Business / Management, Database, Data Mining (EDV), Wirtschaft / Finanzen, Kredit, Management spezifischer Bereiche, Data analysis; Machine learning; Neural networks