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Customer churn, where customers leave a service provider for a competitor, poses significant challenges for telecom companies. This project develops a predictive model using a dataset of 100,000 records with 100 variables, aiming to identify likely churners and provide actionable insights to enhance retention strategies
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Jul 1, 2024 - Jupyter Notebook
This machine learning model was developed for "House Prices - Advanced Regression Techniques" competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.
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Feb 5, 2022 - Jupyter Notebook
How to build, train, and evaluate a Generative Adversarial Network (GAN) for generating fashion images. The project covers all essential steps, from model building to training and evaluation.
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Nov 18, 2024 - Jupyter Notebook
Config files for my GitHub profile.
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Jun 7, 2024
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