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Big Data Analysis

By: Contributor(s): Material type: TextTextPublication details: New Delhi Wiley India (P) Ltd. New Delhi , 2023Edition: 2nd edDescription: 314pISBN:
  • 9788126565757
Subject(s): DDC classification:
  • 006.312 SHA
Summary: The goal of this book is to cover foundational techniques and tools required for Big Data Analytics. It focuses on concepts, principles and techniques applicable to any technology environment and industry and establishes a baseline that can be enhanced further by additional real-world experience. This book aims to be a ready reckoner to either a novice or a professional working in the field. Topics covered include Hadoop, MapReduce, Association Rules, Large-Scale Supervised Machine Learning, Data Streams, Clustering, NoSQL systems (Pig, Hive) and Applications including Recommendation Systems, Web and Security.
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Item type Current library Call number Materials specified Status Date due Barcode
Books Books Indus University Library (IULIB) 006.312 SHA (Browse shelf(Opens below)) Checked out to Shrey Shah (IU2453000045) 20/02/2025 MCA02509
Books Books Indus University Library (IULIB) 006.312 SHA (Browse shelf(Opens below)) In transit from Indus University Library (IULIB) to Indus Institute of Information and Communication Technology (IIICT) since 23/01/2025 MCA02510
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006.312 SHA Big Data Analytics 006.312 SHA Big Data Analytics 006.312 SHA Big Data Analytics 006.312 SHA Big Data Analysis 006.312 SHA Big Data Analysis 006.32 ERL Big Data Fundamentals 006.32 ERL Big Data Fundamentals

The goal of this book is to cover foundational techniques and tools required for Big Data Analytics. It focuses on concepts, principles and techniques applicable to any technology environment and industry and establishes a baseline that can be enhanced further by additional real-world experience. This book aims to be a ready reckoner to either a novice or a professional working in the field. Topics covered include Hadoop, MapReduce, Association Rules, Large-Scale Supervised Machine Learning, Data Streams, Clustering, NoSQL systems (Pig, Hive) and Applications including Recommendation Systems, Web and Security.

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