Curriculum
- 2 Sections
- 19 Lessons
- Lifetime
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- Understanding Problem Statement and Regression Algorithms used in the Project14
- 1.1Project Overview [Video]12 Minutes
- 1.2What is Market Mix Modelling10 Minutes
- 1.3Project Data and Scope [Video]15 Minutes
- 1.4Step-by-Step Approach10 Minutes
- 1.5Influence of Outliers in Predictor Features10 Minutes
- 1.6Support Vector Regression10 Minutes
- 1.7AdaBoost Regressor15 Minutes
- 1.8XGBoost Regressor10 Minutes
- 1.9Random Forest Regressor15 Minutes
- 1.10Decision Tree Regressor10 Minutes
- 1.11Gradient Boosting Regressor10 Minutes
- 1.12KNeighbors Regressor15 Minutes
- 1.13MLPRegressor10 Minutes
- 1.14Introducing polynomial features into a linear regression model
- Code Walkthrough5
Model Building, Optimisation and Elasticity Analysis [Video]
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