Mailorder Service - Data Science Case Study

Table of Contents

• What Is This Projecy About?
• File Structure
• Requirments
• Installation
• Conclusion

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What Is This Projecy About?

This case study is based on real life project given by Bertelsmann/Arvato Financial Services located in Germany and Udacity as a capstone project of Data Science Nano Degree. This project is also about Unsupervised learning and customer segmentation.

This project is divided in below mentioned three major parts :-

1. Customer Segmentation :- Analyze the demographic data of the general population and the current customers using Unsupervised learning techniques.

2. Supervised Learning Model :- Preprocess the given training data based on previous analysis done in customer segmentation part and train the machine learning model that predicts whether or not each individual will respond to the campaign.

3. Kaggle Competition :- Use trained machine learning model on given campaign data to do the predictions as a Kaggle competition.

File Structure

    .
    ├── Arvato Project Workbook.ipynb
    ├── Arvato-Bertelsmann_customer_churning.html
    ├── EDA and Data wrangling.html
    ├── EDA and Data wrangling.ipynb
    ├── README.md
    └── requirements.txt

• Files
  • Arvato Project Workbook.ipynb :- Main notebook of this project
  • Arvato-Bertelsmann_customer_churning.html :- HTML format of the main notebook
  • EDA and Data wrangling.html :- Data Analysis and Data clensing noteboo

Requirements

Python 3.5+, python-pip, pandas , numpy, scikit-learn, seaborn

Installation

install all above necessary requirements and python libraries:

  $ pip install -r requirements.txt

Conclusion

    This real life project provided by Mail-Order service, was to create the customer 
    segmentation using the general population of Germany. This analysis could be helpful for
    marketing team to target individuals who are more likely to be interested in their 
    Mail-Order service.