This jupyter notebook includes end-to-end steps for data understanding and model training.
- Data Understanding & Preparation
- Data Exploration & Analysis
- Model Building
- Business Recommendations
For data analysis, UNIVARIATE BIVARIATE & MULTIVARIATE analysis were done in order to understand the given data and also to get the insights from data.
For model training, I've used different models such as Decision Tree Classifier, Random Forest Classifier, Bagging, Adaboost, Gradient Boosting and Stacking classifier.
After successfull training of all models, I found Adaboost model with hyper parameter tuned worked better on the given dataset.