ML Random Forest

Intermediate Level

02:27 hrs

What you will learn:

Explore the fundamentals of Random Forest as an ensemble method.Differentiate between decision trees and Random Forest models.Apply hyperparameter tuning to optimize Random Forest performance.Evaluate model accuracy using key performance metrics.Interpret feature importance to enhance model insights.

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330 edCoins bonus

1244 Enrolled

3 Rating

Skills you will gain

Random ForestEnsemble LearningDecision TreesHyperparameter TuningModel EvaluationEvaluation MetricsFeature Importance

Overview of Random Forest

Decision Trees Explained

Hyperparameter Tuning

Model Evaluation Techniques

ML Random Forest

Course Modules

1. Overview of Random Forest23 mins60 Edcoins

2. Decision Trees Explained38 mins90 Edcoins

3. Hyperparameter Tuning38 mins90 Edcoins

4. Model Evaluation Techniques42 mins90 Edcoins