Lecture Notes || SNS Courseware

Subject Details

Dept : IT

Sem : 6

Regul : 2017

Faculty : ashokkumar

phone : NIL

E-mail : ashok.r.it@snsce.ac.in

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Lecture Notes

UNIT 1:

Evolution of Big data - Best Practices for Big data Analytics

Big data characteristics - Validating

The Promotion of the Value of Big Data - Big Data Use Cases

Characteristics of Big Data Applications

Perception and Quantification of Value

Understanding Big Data Storage

A General Overview of High-Performance Architecture - HDFS

MapReduce and YARN

Map Reduce Programming Model

UNIT 1 NOTES

UNIT 2:

Advanced Analytical Theory and Methods: Overview of Clustering

K-means - Use Cases

Overview of the Method - Determining the Number of Clusters

Diagnostics - Reasons to Choose and Cautions

Classification: Decision Trees - Overview of a Decision Tree

The General Algorithm

Decision Tree Algorithms - Evaluating a Decision Tree

- Decision Trees in R - Naïve Bayes - Bayes‘ Theorem

Naïve Bayes Classifier.

UNIT 2 NOTES

UNIT 3:

UNIT 3 NOTES

Advanced Analytical Theory and Methods: Association Rules

Evaluation of Candidate Rules

Applications of Association Rules

Evaluation of Candidate Rules

Recommendation System: Collaborative Recommendation

Content Based Recommendation

Knowledge Based Recommendation

Hybrid Recommendation Approaches

Apriori Algorithm

UNIT 4:

UNIT 4 NOTES

UNIT 5:

UNIT 5 NOTES

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