Anubhav Lohani
This project aims to create a model that is able to predict whether a customer would purchase car insurance based on a number of parameters (such as, whether they have a home insurance, what is their occupation, etc.).
Data Preparation: pandas, numpy
Data Exploration: matplotlib, seaborn
Model Selection: scikit-learn
Week 1: Exploratory data analysis on the given dataset. This included cleaning the data (by handling missing values, etc.) and preparing it for visualization.
Week 2: Data visualization. This included plotting charts of the cleaned data to gain insights about trends in the data.
Week 3: Model selection and training. This included selecting different models, training them using the cleaned data and testing for their scores.