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Can I read Machine Learning for Big Data Analysis (Frontiers in Computational Intelligence, 1) on EtoBox?
Machine Learning for Big Data Analysis (Frontiers in Computational Intelligence, 1) by Bhattacharyya, Siddhartha (editor);Bhaumik, Hrishikesh (editor);Mukherjee, Anirban (editor);De, Sourav (editor) is a nonfiction available to read on EtoBox.
What is Machine Learning for Big Data Analysis (Frontiers in Computational Intelligence, 1) about?
This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. Big data analytics is the process of examining large and varied data sets - i.e., big data - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series __Frontiers In Computational Intelligence__ is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational int
Who reads Machine Learning for Big Data Analysis (Frontiers in Computational Intelligence, 1)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Bhattacharyya, Siddhartha (editor);Bhaumik, Hrishikesh (editor);Mukherjee, Anirban (editor);De, Sourav (editor)
- Publisher
- de Gruyter GmbH, Walter
- Published
- 2018
- Language
- EN
- ISBN
- 9783110550771
- Category
- nonfiction
- Subjects
- Computer Science, Engineering, Programming
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