The project has three major steps: the customer segmentation report, the supervised learning model, and the Kaggle Competition.

1. Customer Segmentation Report You'll begin the project by using unsupervised learning methods to analyze attributes of established customers and the general population in order to create customer segments.

2. Supervised Learning Model You'll have access to a third dataset with attributes from targets of a mail order campaign. You'll use the previous analysis to build a machine learning model that predicts whether or not each individual will respond to the campaign.

3. Kaggle Competition Once you've chosen a model, you'll use it to make predictions on the campaign data as part of a Kaggle Competition. You'll rank the individuals by how likely they are to convert to being a customer, and see how your modeling skills measure up against your fellow students.

link of my article about this project on Meduim https://eljazary.medium.com/identify-customer-segmentation-1f994563e0bb

#installation

• pip install -U scikit-learn

in business not all customer have the same criteria and as follow not all customers will be keen to interact with product with the same value , so companies tries to know more about its customers by some different of analysis and emerging technologies like deep Learning and Statistics

Customer segmentation : Customer segmentation is the process of dividing customers into groups based on common characteristics so companies can market to each group effectively and appropriately.

so we will try to grouping Customer according to its similar criteria by using types of machine learning like Clustering and PCA .