Bridgei2i Analytics Solutions Analytics Consultant Interview Questions and Answers

Random Forest and XGBoost are both ensemble learning algorithms used for classification and regression tasks.

• Random Forest is a bagging algorithm that builds multiple decision trees and combines their outputs to make a final prediction.

• XGBoost is a boosting algorithm that builds decision trees sequentially, with each tree correcting the errors of the previous one.

• Random Forest is less prone to overfitting and can handl...read more

Random Forest is an ensemble of Decision Trees that improves accuracy and reduces overfitting.

• Decision Trees are simple and easy to interpret, but prone to overfitting.

• Random Forest combines multiple Decision Trees to reduce overfitting and improve accuracy.

• Random Forest can handle missing values and outliers better than Decision Trees.

• Decision Trees are faster to train and predict than Random Forest.

• Random Forest is s...read more

I have experience in developing AI models for predictive analytics and natural language processing.

• Developed predictive models for customer churn and sales forecasting using machine learning algorithms

• Built chatbots using natural language processing techniques to improve customer service

• Implemented computer vision models for image recognition in retail industry

• Used deep learning models for sentiment analysis of social ...read more