Added the customer churn prediction project scripts.

[prajuktadey]

The issue was assigned to me.

#73: Customer Churn Prediction using ANNs.

• Info about the related issue
  A customer churn model using Artificial Neural Networks (ANN) is a predictive model that aims to identify customers who are at risk of leaving a business or discontinuing their services. The model utilizes ANN, a machine learning technique inspired by the human brain's neural structure, to analyze various customer-related data and predict the likelihood of churn.

• GSSOC Participant

• Contributor

Closes: #73

Describe the changes you've made

I have added the .ipynb scripts and the trained ANN model. I have also made a folder that contains all the data visualizations and there are two files under the Notebooks folder. The Churn Prediction 2.0 contains the data visualization scripts as well.

Type of change

Added the Customer Churn Prediction Project.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested?

Describe how have you verified the changes made

Checklist:

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added tests that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

Screenshots

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