Project on ML - Random Forest Algorithm

Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.

Through this training, we are going to learn and apply how the random forest algorithm works and several other important things about it.

The course includes the following;

• Extract the Data to the platform.
• Apply data Transformation.
• Bifurcate Data into Training and Testing Data sets.
• Built Random Forest Model on Training Data set.
• Predict using Testing Data set.
• Validate the Model Performance.
• Improve the model Performance using Random Forest.
• Predict and Validate the Performance of the Model.

Target Customers:

• Aspiring Data Scientists
• Artificial Intelligence/Machine Learning/ Engineers