---
title: "Discussion on \"Predicting Customer Churn Before It Happens: An End-to-End ML Project with SHAP Explainability\" | Hashnode"
description: "Discussion on \"Predicting Customer Churn Before It Happens: An End-to-End ML Project with SHAP Explainability\". An end-to-end churn prediction pipeline using XGBoost and SHAP for explainability — deployed on both Streamlit Cloud and HuggingFace Spaces. Covers EDA insights, feature engineering, model comparison, and a real Docker deployment debugging story."
url: "https://hashnode.com/posts/predicting-customer-churn-before-it-happens-an-end-to-end-ml-project-with-shap-explainability/6a4925fd5d6713cccaed3468"
---

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# [Predicting Customer Churn Before It Happens: An End-to-End ML Project with SHAP Explainability](https://akshayetukurihashnodedev.hashnode.dev/predicting-customer-churn-before-it-happens-an-end-to-end-ml-project-with-shap-explainability?utm_source=hashnode&utm_medium=feed)

An end-to-end churn prediction pipeline using XGBoost and SHAP for explainability — deployed on both Streamlit Cloud and HuggingFace Spaces. Covers EDA insights, feature engineering, model comparison, and a real Docker deployment debugging story.

Jul 4 · 6 min read · akshayetukurihashnodedev.hashnode.dev  
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-   [#data-science](https://hashnode.com/tag/data-science)
-   [#python](https://hashnode.com/tag/python)
-   [#xgboost](https://hashnode.com/tag/xgboost)
-   [#streamlit](https://hashnode.com/tag/streamlit)

## Written by

[AKSHAY](https://hashnode.com/@akshayetukuri)

@akshayetukuri · Hyderabad, India

  
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