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Course Curriculum

Linear Regression
Correlation vs Regression 00:00:00
First Regression in Python 00:00:00
Geometrical Representation of the Linear Regression Model 3 00:00:00
How to Interpret the Regression Table 00:00:00
Introduction to Regression Analysis 00:00:00
Python Packages Installation 00:00:00
R-Squared 00:00:00
Using Seaborn for Graphs 00:00:00
Welcome to Advanced Statistics! 00:00:00
What is the OLS 00:00:00
Multiple LIinear Regression
A1 Linearity 00:00:00
A2 No Endogeneity 00:00:00
A3 Normality and Homoscedasticity 00:00:00
A4 No Autocorrelation 00:00:00
A5 No Multicollinearity 00:00:00
Adjusted R-Squared 00:00:00
Dealing with Categorical Data – Dummy Variables 00:00:00
Making Predictions with the Linear Regression 00:00:00
Multiple Linear Regression with sklearn 00:00:00
OLS Assumptions 00:00:00
Test for Significance of the Model (F-Test) 00:00:00
Linear Regression with Sklearn
Creating a Summary Table with the p-values 00:00:00
Feature Scaling 00:00:00
Feature Selection through p-values (F-regression) 00:00:00
Game Plan for sklearn 00:00:00
Multiple Linear Regression with sklearn 00:00:00
Simple Linear Regression with sklearn – Summary Table 365 D 00:00:00
Simple Linear Regression with sklearn 00:00:00
Training and Testing 00:00:00
Underfitting and Overfitting 00:00:00
What is sklearn 00:00:00
Linear Regression - Practical Example
Practical Example (Part 1) 00:00:00
Practical Example (Part 2) 00:00:00
Practical Example (Part 3) 00:00:00
Practical Example (Part 4) 00:00:00
Practical Example (Part 5) 00:00:00
Logistic Regression Tommorow
A Simple Example in Python 00:00:00
An Invaluable Coding Tip 00:00:00
Binary Predictors in a Logistic Regression 00:00:00
Building a Logistic Regression 00:00:00
Calculating the Accuracy of the Model 00:00:00
Introduction to Logistic Regression 00:00:00
Logistic vs Logit Function 00:00:00
Testing the Model 00:00:00
Underfitting and Overfitting 00:00:00
Understanding Logistic Regression Tables 00:00:00
What do the Odds Actually Mean 00:00:00
Cluster Analysis (Basics & Prerequisites)
Difference between Classification and Clustering 00:00:00
Introduction to Cluster Analysis 00:00:00
Math Prerequisites 00:00:00
Some Examples of Clusters 00:00:00

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