Data Science Videos

Business Statistics (60)

Data representation
Measures of Central Tendency
Probability Distributions

Cluster Analysis (10)

Details about Cluster Analysis, Hierarchical method of clustering
K- Clustering

Linear, Utility & Safety (10)

Intoduction to
Linaer program
Utility analysis
Safety first principle

Python (3)

Fundamentals
Demo for distribution

Hypothesis Testing (7)

Sample test
Errors in Hypothesis testing

ANOVA (3)

Introduction about Anova
Two way of Anova

Optimization (8)

Description of Optimization

simplex method (11)

Full details about Simplex method

Chi - Square (3)

Full details about Chi - Square
Chi-Square Goodness of Fit Test

Transportation problem (6)

Over all concept of Transportation problem

Probability (5)

Introduction to
Probability distributions

Linear & Logistic Regression (7)

Linear regression models
Performance of logistic model

Reliability based optimization (6)

Reliability based optimization
Sequential optimization
Reliability stochastic optimization

Business Analystics & Data Mining Modelling Using R (80)

Visualization Techniques
Dimension reduction techniques
Performance matrics
Multiple linear regression
Machine learning technique
Naive bayes
Regression trees & types
Cluster analysis

Integer & Quadratic Programming (5)

Integer programming
Quadratic programming

Sampling Distribution (1)

Introducrion about Sampling Distribution

Estimation, Prediction of Regression Model (2)

Estimation, Prediction of Regression Model Residual Analysis

Business & Sustainable development (8)

Data representation
Measures of Central Tendency
Probability Distributions

Business Analytics & Data Mining Modelling Using R Part I (60)

VISUALIZATION
PERFORMANCE

Business Analytics & Data Mining Modelling Using R Part II (20)

Association Rules
Cluster Analysis
Regression Based Forecasting Methods
Understanding Time Series

Business Analytics & Text Mining Modeling Using Python (40)

Built in Capabilities of Python
Database Using Python Pandas
Numerical Python
Python for Analytics

Data Science for Engineers (41)

Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors
Multiple Linear Regression Modelling Building and Selection
Simple Linear Regression Model Assessment

Decision Making Under Uncertainty (33)

Costs, Ratings, Options and Choices for both Restaurants
Expected Value Mean, Variance and Functions
Probability Events, Conditioning and Total Probability

Descriptive Predictive & Prescriptive (27)

Analytics for Decision Making Support
Decision Needs and Analytics
Business Intelligence & Analytics

Econometric Modelling (15)

Formulation of Econometric Modelling
Assumptions of Classical Linear Regression
The Simplest Math Problem No One Can Solve

Tech Forecasting for strategic decision making(35)

Alternatives to forecasting in scope of technology management
Famous forecasts which missed the mark
Introduction to Tech Forecasting for Strategic Decision Making

Attribute selection Measures in CART

Introduction about Attribute selection Measures in CART

Categorical variable regression

Details of Categorical variable regression

Central Tendency and Dispersion

Central Tendency and Dispersion Introduction - Part I

Central Tendency and Dispersion

Central Tendency and Dispersion - Part II

Classification and Regression Trees (CART _ I)

Classification and Regression Trees

Classification and Regression Trees (CART) - III

Classification and Regression Trees

Confidence interval estimation_ Single population - I

Confidence interval estimation_ Single population Introduction

Confidence interval estimation_ Single population - II (1)

Confidence interval estimation_ Single population functioning

Confusion matrix and ROC- I

Confusion Matrix and ROC Introduction

Confusion Matrix and ROC-II

Confusion Matrix and ROC Experiment

Distribution of Sample Means, population, and variance

Distribution of Sample Means, population, and variance

Lecture 36

DEA Introducrion

Lecture 37_ DEA

DEA Part -1

Lecture 38_ DEA

DEA Part - 2

Lecture 39_ Gomory cutting plane algorithm

Gomory cutting plane algorithm full details

Lecture 40_ Gomory cutting plane algorithm

Gomory cutting plane algorithm

Portfolio optimization I

Portfolio optimization

Chance constraint problem (1)

Chance constraint problem

Lecture 47_ branch and bound (1)

Branch and bound

Lecture 48_ branch and bound (1)

Branch and bound

Lecture 49_ branch and bound (1)

Branch and bound

Lecture 50_ branch and bound (1)

Branch and bound

Steepest descent (1)

Steepest descent

Robustness I

Robustness - Introduction

Robustness II

Robustness

Maximum Likelihood Estimation-I

Maximum Likelihood Estimation - Introduction

Maximum Likelihood Estimation-II

Maximum Likelihood Estimation - Programming

Measures of attribute selection

Measures of attribute selection - Introduction

MULTIPLE REGRESSION MODEL-I

Introduction about Multiple regression model

MULTIPLE REGRESSION MODEL-II

Multiple regression model

Post Hoc Analysis

Introduction about Post Hoc Analysis

RBD

Randomize block design (RBD)

Regression Analysis Model Building - I

Regression Analysis Model Building Introduction

Regression Analysis Model Building - II (1)

Regression Analysis Model Building details