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This project focuses on forecasting customer churn in the telecom industry by leveraging various features. The goal is to implement a straightforward, real-time prediction system capable of handling both batch and online predictions. The predictive model is deployed using Streamlit, providing an interactive and user-friendly interface for exploring

Home Page: https://appapppy-yq4zcdcq8wnggnqtk93bff.streamlit.app/

License: GNU General Public License v3.0

Python 1.81% Jupyter Notebook 87.87% CSS 9.35% JavaScript 0.05% HTML 0.92%
dagshub data-science dvc dvc-pipeline machine-learning mlflow streamlit

customerchurn's Introduction

Hi 👋, I'm Govardhan Vembadi

As a student, I am an aspiring machine learning engineer.

govardhan211103

  • 🔭 I’m currently working on Data Version Control.

  • 🌱 I’m currently learning MLOps

  • 📝 I regularly write articles on https://medium.com/@govardhanv

  • 💬 Ask me about Machine Learning, MLOps, Data Analysis, Python,

  • 📫 How to reach me [email protected]

Blogs posts

Connect with me:

govardhanv govardhan___v 21241a0560 govardhan_1

Languages and Tools:

c css3 git html5 java pandas python scikit_learn seaborn seaborn

govardhan211103

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