02:13

directed graphs

03:27

Simple Graphs

04:10

Complex network analysis

02:08

Social network analysis

03:08

data cleaning (Course Promo)

03:22

Handling Missing Values and Noise Values (Univariate Outliers)

05:30

feature types

27:54

Language basic analytics (Roman Burushaski)

06:19

Endangered Languages (Burushaski)

41:18

Text Preprocessing, NLP

51:07

RM L4: Writing Literature review, proposed work and experimental results

39:32

WP L12: Jquery Animate

57:39

WP L11: JQuery

02:35:35

NLP L5: Topic Modeling

01:42:51

RM L3: Reading / Writing Abstract, Introduction and Literature Review

01:07:53

WP L9: Javascript

01:11:44

WP L8: Javascript

02:56:32

NLP L4: Text Vectorization and Text Categorization

01:48:27

WP L7: Cascading stylesheets

01:28:36

RM L2: Starting a research degree

01:11:44

WP L8: Javascript

01:21:53

WP L6: Cascading stylesheets

01:35:19

RM L1: Basic discussion

59:28

WP L3: Web Technologies and Web application architecture

02:23:47

NLP Fall21: L1. Introduction

56:41

WP L2: History of Internet and Worldwide web

56:29

WP, L1: Overview and outline (Urdu / English)

14:05

Link Analysis: Betweenness centrality

10:08

Network Analysis: Link Analysis using closeness centrality

05:06

MLDS MID Q5 Answer: Calculating Precision and Recall from Confusion Matrix

09:48

MLDS MID Q4 Answer: Naive bayes classifier, label prediction on sample data

05:38

MLDS MID Q3 Answer: Univariate outliers detection and handling

10:40

MLDS MID Q2 Answer: Classification with K-Nearest Neighbors and Decision Tree Algorithms

05:30

MLDS MID Q1 Answer: Visualizing the outcome of clustering models on given data

31:23

Programming in C++: Operator Overloading

01:10:00

SNA: Graph Analysis and Visualization with Gephi

01:23:40

SNA: Behavior Analysis

42:51

NLP: Syntagmatic Word Association

01:28:36

MLDS: Feature Engineering

32:10

Programming in C++: Polymorphism and Inheritance type

01:02:05

NLP: Paradigmatic Word Associations (Urdu/Hindi)

01:24:33

Social Network Analysis: Information Theory (Urdu/Hindi)

28:49

Programming in C++: Polymorophism, Inheritance type (Urdu/Hindi)

01:31:13

Social Network Analysis: Information Diffusion, Explicit and Implicit Networks (Urdu/Hindi)

01:33:55

Machine Learning: Linear and Logistic Regression (Urdu/Hindi)

01:02:57

Programming in C++: Virtual and Pure Virtual Functions (Urdu/Hindi)

31:14

Social Network Analysis: Information Diffusion (Herd Behavior) in Urdu/Hindi

33:57

Network Analysis Project Pipeline (Urdu/Hindi)

50:27

Programming in C++: Inheritance Implementation (Urdu/Hindi)

48:26

MLDS discussion: Agglomerative clustering, divisive clustering, Validation and Evaluation

42:32

Programming in C++: Inheritance

36:02

Programming in C++: Copy constructor, Objects in parameters, destructor, Private member functions

45:49

SNA: Community Evaluation

30:19

Programming in C++: Coding of Classes and Constructors

26:22

Programming in C++: Constructors

37:46

Machine Learning: Discussion on Clustering and Classification (Urdu/Hindi_

52:40

Programming in C++: Classes (Urdu/Hindi)

01:16:01

Social Network Analysis: Network Community Detection (Urdu/Hindi)

36:58

Programming in C++: Structures

12:54

Social Network Analysis Kempe Graph Coloring Algorithm