Big Data Analytics
- Publisher: PHI
- ISBN-13: 9788120351165
- Pages: 250
- Binding: Paperback
- Year of Pub / Reprint Year: 2016
About The Book
The book is an unstructured data mining quest, which takes the reader through different features of unstructured data mining while unfolding the practical facets of Big Data. It emphasizes more on machine learning and mining methods required for processing and decision-making. The text begins with the introduction to the subject and explores the concept of data mining methods and models along with the applications. It then goes into detail on other aspects of Big Data analytics, such as clustering, incremental learning, multi-label association and knowledge representation. The readers are also made familiar with business analytics to create value. The book finally ends with a discussion on the areas where research can be explored.
The book is designed for the senior level undergraduate, and postgraduate students of computer science and engineering.
Table Of Contents
2. Data Mining and Modelling
3. Big Data Mining—Application Perspective
4. Long Live the King of Big Data: The Context
5. Big Data Text Categorization and Topic Modelling
6. Multi-label Big Data Mining
7. Distributed High Dimensional Data Clustering for Big Data
8. Machine Learning and Incremental Learning with Big Data
9. Analytics in Today’s Business World
• Contains numerous examples and case studies.
• Discusses Apache’s Hadoop—a software framework that enables distributed processing of large datasets across the clusters of computing machines.
• Incorporates review questions, MCQs, laboratory assignments and critical thinking questions at the end of the chapters, wherever required.
About The Authors
Parag Kulkarni, PhD, is CEO and Chief Scientist, EKLaT Research, Pune. Dr. Kulkarni is an entrepreneur, machine learning expert and innovation strategist. Through his consultations and innovative leadership, he has turned around fortune of more than one dozen start-ups in last two decades. He is pioneer of concepts systemic machine learning and systemic knowledge innovation. He is visiting researcher and faculty at various B-schools and technical schools of repute, including IITs, IIMs, Masaryk University, COEP, etc. Besides being the co-author of more than half a dozen books, he has also authored two books, namely, Knowledge Innovation Strategy and Reinforcement and Systemic Machine Learning for Decision Making as well as more than 220 research papers. Dr. Kulkarni is co-inventor of half a dozen patents as well. He has delivered more than 100 keynote addresses and numerous talks on machine learning, strategy and managing start-ups to deliver extraordinary impact on strategic perspective of thousands of researchers and professionals. He has worked very closely with Grassroots innovators and contributed to Grassroots innovations through his refreshing novel ideas in the fields of artificial intelligence and machine learning. His areas of interests include artificial intelligence, machine learning, business and knowledge innovation and data mining.
Sarang Joshi, PhD, is Professor at Pune Institute of Computer Technology (PICT), Pune. He was the chairman of board of studies and member of academic council, Savitribai Phule Pune University (SPPU), formally Pune University. Professor Joshi’s areas of interest include visualization, virtualization algorithms and data processing.
Meta S. Brown is President of A4A Brown Inc.—a boutique consultancy that helps technical people to communicate with executives and clients. She is the author of Data Mining for Dummies, and creator of the storytelling for Data Analysts and Tech Workshops. Her areas of interest include business analytics and text analytics.