Actions for Big Data Analytics Methods : Analytics Techniques in Data Mining, Deep Learning and Natural Language Processing
Big Data Analytics Methods : Analytics Techniques in Data Mining, Deep Learning and Natural Language Processing / Peter Ghavami
- Author
- Ghavami, Peter K.
- Published
- Berlin ; Boston : De Gruyter, [2019]
- Copyright Date
- ©2020
- Edition
- 2nd Edition.
- Physical Description
- 1 online resource (XVI, 238 pages)
Access Online
- Language Note
- In English.
- Contents
- Frontmatter -- Acknowledgments -- About the Author -- Contents -- Introduction -- Part I: Big Data Analytics -- Chapter 1. Data Analytics Overview -- Chapter 2. Basic Data Analysis -- Chapter 3. Data Analytics Process -- Part II: Advanced Analytics Methods -- Chapter 4. Natural Language Processing -- Chapter 5. Quantitative Analysis{u2014}Prediction and Prognostics -- Chapter 6. Advanced Analytics and Predictive Modeling -- Chapter 7. Ensemble of Models: Data Analytics Prediction Framework -- Chapter 8. Machine Learning, Deep Learning{u2014}Artificial Neural Networks -- Chapter 9. Model Accuracy and Optimization -- Part III: Case Study{u2014}Prediction and Advanced Analytics in Practice -- Chapter 10. Ensemble of Models{u2014}Medical Prediction Case Study: Data Types, Data Requirements and Data Pre-Processing -- Appendices -- References -- Index
- Summary
- 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.
- Subject(s)
- ISBN
- 9781547401567
1547401567
9781547401581
1547401583
9781547417957
1547417951 - Finding Aid Note
- Available in electronic full text to members of the University via the Library web catalogue.
- Digital File Characteristics
- PDF
text file - Bibliography Note
- Includes bibliographical references and index.
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