# jalajthanaki/Customer\_segmentation

<https://repo.masters-masters.com/en/repos/jalajthanaki/Customer_segmentation>

[Home](https://repo.masters-masters.com/en) › [jalajthanaki](https://repo.masters-masters.com/en/owners/jalajthanaki) › [Customer\_segmentation](https://repo.masters-masters.com/en/repos/jalajthanaki/Customer_segmentation)

jalajthanaki/Customer\_segmentation has 139 stars on GitHub. Its RepoMasters card: Prototype tier. Analysing the content of an E-commerce database that…

| Field | Value |
| --- | --- |
| Owner | [jalajthanaki](https://repo.masters-masters.com/en/owners/jalajthanaki) |
| Stars | 139 |
| Forks | 61 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | None |
| Created | 2018 |
| Topics | customer-segmentation, customer-analytics, e-commerce-example, machine-learning-algorithms, voting-classifier, predictive-analytics |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [jalajthanaki/Customer\_segmentation](https://github.com/jalajthanaki/Customer_segmentation) |

## Repository

Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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