# Pradnya1208/Telecom-Customer-Churn-prediction

<https://repo.masters-masters.com/en/repos/Pradnya1208/Telecom-Customer-Churn-prediction>

[Home](https://repo.masters-masters.com/en) › [Pradnya1208](https://repo.masters-masters.com/en/owners/Pradnya1208) › [Telecom-Customer-Churn-prediction](https://repo.masters-masters.com/en/repos/Pradnya1208/Telecom-Customer-Churn-prediction)

Pradnya1208/Telecom-Customer-Churn-prediction has 122 stars on GitHub. Its RepoMasters card: Prototype tier. Customers in the telecom industry can choose from…

| Field | Value |
| --- | --- |
| Owner | [Pradnya1208](https://repo.masters-masters.com/en/owners/Pradnya1208) |
| Stars | 122 |
| Forks | 35 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | None |
| Created | 2021 |
| Topics | customer-churn-prediction, customer-churn-analysis, classification, classification-algorithm, feature-engineering, cross-validation, model-evaluation, roc-auc, gridsearchcv, sklearn |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [Pradnya1208/Telecom-Customer-Churn-prediction](https://github.com/Pradnya1208/Telecom-Customer-Churn-prediction) |

## Repository

Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.

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

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.