**Problem Statement**
Insurance firms have been running direct marketing efforts through telemarketing to encourage clients to apply for health insurance. So far, we have called all of our target clients, but to save money, we would like to limit the number of calls we make to those most likely to place purchases.

**Task** 
As a data scientist in the digital department of the insurance company, you are asked to output an attack list that predicts whether or not you will receive an order. Create the most accurate model possible. You need to analyse the data and match it with the quantitative result you get. We will see the analysis which you would perform on the data more than the accuracy of the model. Make all the analysis in a jupyter notebook using pandas and numpy library. 

**Rules**
* You must use your team name for submissions
* You are allowed to take inspiration from other sources. Copying any existing implementation directly without understanding will lead to disqualification from the contest. 
* You are allowed to use numpy, pandas and sklearn libraries. 
* Submit the code along with the application through the google form provided below. https://forms.gle/xhToyQ3QTtbUgefo7

**Contact**
If you have any doubts, you can contact:
Vinayak - 9500180979


If you are new to Kaggle Competitions, you can check the below links, which will give you a brief overview of how kaggle competition works.
Here is a handy link to Kaggle's [competition documentation](https://www.kaggle.com/docs/competitions), which includes, among other things, instructions on [submitting predictions](https://www.kaggle.com/docs/competitions#making-a-submission).