Arun Sudheer Email and Phone Number

Business Objective: The objective is to assist an airline organization to satisfy their passengers with the services provided by them,Approach: The methodology for predicting whether a passenger is satisfied by the services provided by an airline involves a series of steps and techniques aimed at developing an accurate predictive model. These steps include Data Pre-processing (Data Cleaning, Missing Value Treatment, Outlier Detection), Feature Selection, Model selection, Training, and Evaluation. Building various classification models such as Logistic regression, AdaBoost, Gradient Boost, Random Forest, XG Boost to predict passenger and achieve the best results (Accuracy, F1-score)Outcome: The best accuracy of approximately 96% is being achieved by both Random Forest and XG boost algorithms after feature selection and hyperparameter tuning.Tools Used: Python, EDA, Supervised Learning, Feature Selection (SFS), Hyper-parameter tuning.Customer Loan Prediction Business Objective: To predict whether a customer is eligible to acquire a loan based on the customers credibility.Approach: The methodology for predicting whether a customer is eligible to acquire a loan typically involves a series of steps and techniques aimed at developing an accurate predictive model. These steps include data pre- processing, feature selection, model selection, training, hyperparameter tuning and evaluation. Building various classification models such as random forest, decision tree, Gradient Boosting, AdaBoost and XG Boost that aim at providing the best results by obtaining the best features via feature selection and other evaluation metrics.Outcome: The best accuracy score of approximately 91% is being achieved by Gradient Boosting algorithm after fine tuning.Tools Used: Python, EDA, Supervised Learning, Hyper-parameter tuning.House Price Prediction Business Objective: To predict the price of a house based on different factors such as street, condition of the house, year sold, utilit