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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.
Big Data Analytics Video Tutorial
Module 1 – Hadoop Distributed File System and Map Reduce Programming
How to install and Configure Hadoop in Ubuntu Step by Step Procedure – Shortcut Method
Components and Architecture Hadoop Distributed File System (HDFS)
What is HDFS? Design Features of HDFS
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.
Architecture and Components of Hadoop Distributed File System (HDFS) – Big Data Analytics
Design Features of Hadoop Distributed File System (HDFS) – Big Data Analytics
Safe Mode Rack Awareness High NameNode Availability NameNodeFederation CheckPoints Backup Snapshots
Block Replication in Hadoop Distributed File System (HDFS) – Big data Analytics
Hadoop MapReduce Model – Big Data Analytics Tutorial
Word Count Program using Python Streaming Interface – Big Data Analytics Tutorial
WordCount Program in C++ using Pipes interface Hadoop MapReduce Model – Big Data Analytics Tutorial
WordCount Program in Java Hadoop MapReduce Model – Big Data Analytics Tutorial
HDFS User Commands – Big Data Analytics Tutorial
How to install and Configure Hadoop in Ubuntu Step by Step Procedure – Shortcut Method
Using the Web GUI to Monitor the MapReduce Running Examples – Big Data Analytics Tutorial
Running Basic Hadoop Benchmarks – Big Data Analytics Tutorial
How to Run Hadoop MapReduce Examples – Big Data Analytics Tutorial
Debugging MapReduce Parallel Application – Big Data Analytics Tutorial
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Module 1 – Big Data Analytics 15CS82 VTU CBCS Notes
Module 2 – Data Processing Tools, Hadoop 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.
Apache Sqoop – Hadoop Ecosystem – Big Data Analytics Tutorial
Apache Spoop steps to Import and Export data between Database and HDFS
Apache Flume Hadoop Ecosystem – Big Data Analytics Tutorial
Apache Pig Hadoop Ecosystem – Big Data Analytics Tutorial
Apache Oozie Hadoop Ecosystem – Big Data Analytics Tutorial
Apache Hive Hadoop Ecosystem – Big Data Analytics Tutorial
Apache HBase Hadoop Ecosystem – Big Data Analytics Tutorial
Apache YARN Resource Manager – Big Data Analytics Tutorial
Hadoop Yarn Administration – Big Data Analytics Tutorial
Apache Ambari GUI Based method to manage Hadoop Services and configuration of Hadoop
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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.
Business Intelligence – Big Data Analytics Tutorial
Business Intelligence Applications – Big Data Analytics Tutorial
Introduction to Data Warehouse – Big Data Analytics Tutorial
Data Warehouse Architecture – Big Data Analytics Tutorial
Introduction to Data Mining – Big data analytics Tutorial
Introduction to Data Mining Techniques – Big Data Analytics Tutorial
Tools and Platforms for Data Mining – Big Data Analytics Tutorial
Cross Industry Standard Process for Data Mining – CRISP-DM – Big Data Analytics Tutorial
Myths and Mistakes in data Mining – Big Data Analytics Tutorial
Data Visualization in Data Mining – Big Data Analytics Tutorial
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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.
Decision Tree with Solved Numerical Example – Big Data Analytics Tutorial
Regression Analysis – Big Data Analytics Tutorial
Linear Regression Numerical Example with one Independent Variable
Linear Regression Numerical Example with Multiple Independent Variables
Linear Regression Numerical Example with one Independent Variable using Microsoft Excel
Linear Regression Numerical Example with Multiple Independent Variable using Microsoft Excel
Introduction to Cluster analysis and K Means Algorithm – Big Data Analytics Tutorial
K Means Clustering Algorithm – Solved Numerical Example – Big Data Analytics Tutorial
An Introduction to Artificial Neural Networks – Big Data AnalyticsTutorial
Introduction to Association Rule Mining and Apriori Algorithm – Big Data Analytics Tutorial
Association Rule Mining – Apriori Algorithm – Numerical Example Solved – Big Data Analytics Tutorial
Association Rule Mining-Apriori Algorithm – Solved Numerical Example
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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.
Text Mining Process Term Document Matrix Advantages Disadvantages of Text Mining
Naïve Bayes Model Big Data Analytics Tutorial by Mahesh Huddar
Solved Example Text Analytics or Text Classification using Naïve Bayes Classifier
Introduction to Support Vector Machine – Big Data Analytics – Machine Learning
Solved Support Vector Machine – Linear SVM Example – Big Data Analytics Tutorial
Solved Support Vector Machine – Non-Linear SVM Example – Big Data Analytics Tutorial
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Frequently asked Pattern Programs in Placement Interview:
Star Pattern Programs in Python, C, C++ (CPP) and Java
Series Pattern programs in Python, C, C++ (CPP) and Java
Number Pattern programs in Python, C, C++ (CPP) and Java
Alphabet / Character Pattern programs in Python, C, C++ (CPP) and Java
Click Here to download BDA Notes
Module 1 – Big Data Analytics 15CS82 VTU CBCS Notes
Module 2 -Data Processing Tools, Haddop and YARN Administration
Module 3 -Business Intelligence, Data Warehousing, Data Mining, Data Visualization
Click the below link to download the 2017 Scheme 17CS82 Big Data Analytics VTU CBCS Notes
8th Semester Computer Science and Engineering Sun Star Exam Scanner
2018 Scheme Computer Science and Engineering VTU CBCS Notes
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