Lecture Notes || SNS Courseware

Subject Details

Dept : CSE

Sem : 4

Regul : R2019

Faculty : Poornima devi L

phone : NIL

E-mail : poornima.l.cse@snsct.org

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Lecture Notes

UNIT 1:

Big Data and Data Science, A Project on Data Analytics

A Little History on Methodologies for Data Analytics

; Data Analytics- Types, Tools and Applications

KDD Process, CRISP-DM Methodology

UNIT 2:

Descriptive Statistics

Scale Types,

Descriptive Univariate Analysis, Descriptive Bivariate Analysis; Descriptive Multivariate Analysis

Multivariate Frequencies, Multivariate Data Visualization, Multivariate Statistics

Infographics and Word Clouds

Data Quality - Missing Values, Redundant Data, Inconsistent Data, Noisy Data, Outliers

UNIT 3:

Distance Measures

Distance Measures for Non-conventional Attributes

Clustering Validation

Clustering Techniques - K-means, Centroids and Distance Measures, DBSCAN

UNIT 4:

Binary Classification

Predictive Performance Measures for Classification

Distance-based Learning Algorithms

K-nearest Neighbor Algorithms, Case-based Reasoning; Probabilistic Classification Algorithms -

Binary Classification

Logistic Regression Algorithm, Naive Bayes Algorithm.

UNIT 5:

Regression and its types

DA Applications for Text, Web and Social Media

Working with Texts, Recommender Systems, Social Network Analysis

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