Ensemble-Learning

EasyVisa Project

• Project completed as part of Great Learning's Postgraduate Program - Data Science and Business Analytics
• Project delivered in December 2021
• Repository includes two files:
  • Jupyter notebook with Python code written for data analysis and model building
  • CSV file includes data imported into notebook

Problem Statement

• Analyze the data of visa applicants, build a predictive model to facilitate the process of approvals, and, based on important factors that significantly influence the status, recommend a suitable profile for the applicants for whom the visa should be certified or denied.

Skills and Tools

• Exploratory Data Analysis (Variable identification, Univariate analysis, Bivariate analysis)
• Data Preprocessing
• Customer Profiling
• Bagging Classifiers (Bagging and Random Forest)
• Boosting Classifier (AdaBoost,Gradient Boosting,XGBoost)
• Stacking Classifier
• Hyperparameter Tuning using GridSearchCV