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Data Science Masterclass with Live Projects & Case Studies
INTRODUCTION TO DATA SCIENCE
Trainer Introduction (2:33)
Introduction to Business Analytics (13:38)
Application of Business Analytics (12:23)
Introduction to Machine Learning (12:31)
How to switch your career into ML (14:56)
How to switch your career into ML #2 (3:31)
INTRODUCTION TO R
Introduction to R (15:07)
Setting up R (11:08)
R Programming
R Operator (13:45)
R Loop (12:02)
R Function (13:20)
R Function #2 (10:10)
R Function part #3 [ Writing Function ] (5:57)
R Data Structure
An Introduction of R Data Structure + Vector (11:13)
Matrix, Array and Data Frame (14:37)
A Deep Drive to R Data Frame (13:02)
Factor (4:12)
List (6:19)
Import and Export in R
Import CSV Data in R (9:26)
Import Text Data in R (3:19)
Import Excel, Web Data in R (12:47)
Export Data in R - Text (4:07)
Export Data in R - CSV & Excel (2:37)
Data Manipulation
Data Manipulation - Apply Function (13:15)
Data Manipulation - select (11:46)
Data Manipulation - mutate (14:28)
Data Manipulation - filter (14:11)
Data Manipulation - arrange (9:38)
Data Manipulation - Pipe Operator (11:26)
Data Manipulation - group by (8:30)
Data Manipulation - Date (10:35)
Data Visualization
Scatter Plot (12:01)
mfrow (7:37)
pch (12:30)
Color (1:19)
Line Chart (3:21)
Bar Plot (7:05)
Pie Chart (6:43)
histogram (7:06)
Density Plot (2:26)
Boxplot (5:01)
Mosaic Plot (7:59)
3D Plot (10:39)
Correlation Plot and Word Cloud (9:02)
ggplot 2-part1 (14:03)
ggplot2-part2 (8:08)
ggplot2-part3 (15:04)
Introduction To Statistics
Intro to Statistics-Part 1 (13:25)
Intro To Statistics -Part2 (8:53)
Intro To Statistics - Part 3 (14:55)
Intro To Statistics -part4 (4:15)
Intro To Statistics -Part 5 (15:09)
Intro To Statistics -Part 6 (8:21)
Intro To Statistics-Part7 (15:04)
Intro To Statistics-Part8 (10:45)
Intro To Statistics - Part9 (10:24)
Intro To Statistics-Part 10 (14:34)
Intro To Statistics -Part11 (7:11)
HYPOTHESIS Testing
Hypothesis Testing Intro -Part 1 (10:08)
Hypothesis Testing Intro -Part 2 (11:28)
Hypothesis Testing Intro -Part 3 (14:21)
Hypothesis Testing Intro -Part 4 (6:01)
Hypothesis Testing in Practice
Hypothesis Testing in Practice-Part 1 (15:04)
Hypothesis Testing in Practice-Part2 (9:36)
Hypothesis Testing In Practice - Part3 (14:16)
Hypothesis Testing in Practice -Part4 (12:36)
Hypothesis Testing in Practice -Part5 (10:29)
Hypothesis Testing in Practice -Part6 (13:46)
Chi Square -Part1 (11:19)
Chi Square -Part2 (14:57)
ANOVA-Part 1 (12:30)
ANOVA-Part 2 (14:20)
Chapter Summary of Hypothesis Testing (5:08)
Machine Learning Toolbox
Machine Learning Toolbox - Part1 (14:00)
Machine Learning Toolbox - Part2 (12:31)
Business Use Case Understaing
Business Case Understanding (12:51)
Data Pre-processing
Data Pre-Processing 1 (14:45)
Data Pre-Processing 2 (14:29)
Data Pre-Processing 3 (10:25)
Data Pre-Processing 4 (9:39)
Data Pre-Processing 5 (12:33)
Data Pre-Processing 6 (7:19)
Data Pre-Processing 7 (15:04)
Supervised Learning: Regression
Linear Regression #1 (11:47)
Linear Regression #2 (14:23)
Linear Regression #3 (20:21)
Linear Regression #4 (19:02)
Linear Regression #5 (25:00)
Linear Regression #6 (15:02)
Linear Regression #7 - [Part 1] (14:31)
Linear Regression #7 - [Part 2] (13:44)
Linear Regression #8 (12:52)
Linear Regression #9 (16:03)
Dummy Variable (12:34)
Non Linear Regression (10:55)
Logistic Regression
Classification Overview (13:29)
Logistics Regression Intuition (14:04)
R Code Implementation - [Part 1] (5:09)
R Code Implementation - [Part2 ] (10:37)
Model Evaluation (12:28)
Telecom Churn Case Study (22:27)
Chapter Summary (6:41)
K-NN
KNN Intuition (13:26)
KNN Case Study (13:59)
KNN R Code Implementation (12:48)
SVM
SVM Intuition (8:44)
SVM R Code Implementation (8:22)
SVM Model Tuning (9:00)
SVM Telecom Case Study (7:56)
SVM Pros and Cons (7:27)
SVM Chapter Summary (3:49)
Naive Bayes
Naive Bayes Intuition (19:56)
Naive Bayes R Code Implementation (8:25)
Naive Bayes Case Study (8:25)
Decision Tree
Decision Tree Intuition (14:54)
How Decision Tree works (7:40)
Decision Tree R Code Implementation (13:44)
Decision Tree Pruning (15:36)
Decision Tree Case Study (14:24)
Random Forest
Random Forest Intuition (11:37)
Random Forest R Code Implementation (5:13)
Random Forest Case Study (10:02)
Capstone Project - Titanic Survival Project
Introduction to the Titanic Survival Project (11:03)
Capstone Project - Data Understanding (5:10)
Capstone Project - Lazy Predictor (7:20)
Capstone Project - Data Preparation (6:12)
Capstone Project - Data Exploration (4:34)
Capstone Project - Feature Engineering (7:33)
Capstone Project - Logistics Regression (16:10)
Capstone Project - Logistics Regression #2 (4:06)
Capstone Project - Decision Tree (18:28)
Capstone Project - Random Forest (3:06)
K-Mean Clustering
Unsupervised Learning Introduction (6:12)
K-Mean Clustering Intuition (19:40)
K-Mean Clustering -R Code Implementation (15:28)
K-Mean Clustering -Case Study (12:04)
Hierarchical Clustering
Hierarchical Clustering Intuition (12:44)
Hierarchical Clustering - R Code Implementation (16:49)
Hierarchical Clustering - Case Study (7:35)
DBScan Clustering
DBScan Clustering - Case Study (8:59)
DBScan Clustering - Intuition and R Code (11:37)
Principal Component Analysis [ PCA ]
PCA Intuition (12:05)
PCA R Code Implementation (16:35)
PCA Case Study (16:39)
Association Rule Mining
Association Rule Mining -Introduction (16:16)
Association Rule Mining - Pre-Processing (7:14)
Association Rule Mining -R Code Implementation (10:56)
Association Rule Mining - Case Study (18:16)
Capstone Project - Big Mart
Big Mart Sale - Data Structure (15:23)
Big Mart Sale - Univariate Analysis (11:14)
Big Mart Sale - Bi-Variate Analysis (7:15)
Big Mart Sale - Fetature Engineering (13:21)
Big Mart Sale - Pre-Processing (19:08)
Big Mart Sale - Model Building & Evaluation (18:18)
Model Deployment
Model Deployment - Workflow (10:01)
Model Deployment - Pre Requisite (9:39)
Model Deployment - Steps To Follow (19:07)
Model Deployment - Azure ML DEMO (11:06)
Hierarchical Clustering - R Code Implementation
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