Curriculum
- 2 Sections
- 22 Lessons
- 7 Days
Expand all sectionsCollapse all sections
- Getting Started, EDA and Pre-Processing11
- 1.1Project Overview [Video]8 Minutes
- 1.2Project Objectives5 Minutes
- 1.3Learning Objectives
- 1.4Study Guide5 Minutes
- 1.5How to go about5 Minutes
- 1.6Setting up your Environment10 Minutes
- 1.7About the Input Data [Video]10 Minutes
- 1.8EDA and Pre-processing [Video]10 Minutes
- 1.9EDA Coding [Video]20 Minutes
- 1.10Class Imbalance and SMOTE
- 1.11Train-Test Split
- Random Forest Modelling and Evaluation11
- 2.2What is Random Forest?10 Minutes
- 2.3Random Forest Training Process12 Minutes
- 2.4Decision Tree Concepts [Video]20 Minutes
- 2.5Random Forest Explained [Video]
- 2.6Classification Errors and Metrics [Video]10 Minutes
- 2.7Understanding Classification Metrics [Video]15 Minutes
- 2.8Hyperparameter Tuning in Random Forest (Pruning)
- 2.9Random Forest Modelling – Coding [Video]30 Minutes
- 2.10Understand Grid-Search Cross Validation15 Minutes
- 2.11Feature Importance in Random Forest15 Minutes
- 2.12Python Code for Project
Feature Importance in Random Forest
Prev