Star Bucks Project

This is an classification model which predicts whether a customer will respond to an offer or not.

Installation

1. Python3.6
2. Pandas
3. NumPy
4. Matplotlib
5. Seaborn
6. sklearn

Motivation

The problem is to build a model that predicts whether a customer will respond to an offer or not.

Files in the repository

1. data : The dataset file.
2. Starbucks_Capstone_notebook.ipynb : Notebook file contaning the exploration and analysis of the work.
3. README.md : The readme file for write-up.

Summary of the results

Here we are predicting if a customer will respond to the offer or not. It will be very helpful in business perspective. By predicting, we can able to give customer some other offers so that there will be more profit.

Prediction is divided into the following steps

1. Reading Dataset
2. EDA
3. Data pre-processing
4. Feature Selection
5. Modelling
6. Evaluation

How to interact with your project?

Here you just need to install python and install the packages that are listed above and open this .ipymb file in your jupyter notebook and just run all cell or just click SHIFT + ENTER to run cell one by one.

Licensing

This is just for learning.

Authors

Biswajit Satapathy Jr. Data Analyst Aptus Data Labs

Acknowledgement

Special thanks to Pramit Kumar Patra for giving his valuable time for teaching me statistics and machine learning.