Big Data Analytics 15CS82 VTU CBCS Notes
Download VU CBCS notes of Big Data Analytics 15CS82 VTU CBCS Notes for 8th-semester computer science and engineering, VTU Belagavi.
Module 1 – Hadoop Distributed File System and Map Reduce Programming
Following are the contents of module 1 – HDFS
In this module, you will learn the concepts of Hadoop Distributed File System Basics (HDFS). You will understand, how to run map reduce example programs and benchmarks on HDFS. Also, you will study the Hadoop MapReduce Framework. Finally, simple MapReduce Programming examples are discussed in Java, C++, and python.
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Module 1 – Big Data Analytics 15CS82 VTU CBCS Notes
Module 2 – Data Processing Tools, Haddop and YARN Administration
Following are the contents of module 2
In this module, you will study Essential Hadoop Tools such as Apache Pig, Apache Hive, Apache HBase, Apache Sqoop, and Apache Oozie. Also, Hadoop YARN Applications, Managing Hadoop with Apache Ambari, Basic Hadoop Administration Procedures are discussed.
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Module 2 -Data Processing Tools, Haddop and YARN Administration
Module 3 – Business Intelligence, Data Warehousing, Data Mining, Data Visualization
Following are the contents of module 3
In this module, you will study, business Intelligence Concepts and their applications. Important concepts such as Data Warehousing, Data Visualization, and Data Mining are discussed.
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Module 3 -Business Intelligence, Data Warehousing, Data Mining, Data Visualization
Module 4 – Decision Trees, Regression, Artificial Neural Networks, Cluster Analysis, Association Rule Mining
In module 4, different machine learning algorithms such as Decision Trees, Regression, Artificial Neural Networks, Cluster Analysis, Association Rule Mining are discussed.
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Module 5 – Text Mining, Naïve Bayes Analysis, Support Vector Machine, Web Mining, and Social Network Analysis
In module 5, important concepts of Text Mining discussed. Later how to apply Naïve-Bayes Analysis on sample textual data for classification discussed. The concepts of Support Vector Machines are discussed in detail. Finally, you will understand, how Web Mining and Social Network Analysis are performed
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