PS : This is a temporary repository of UmojaHack Expresso code for validation by Zindi.
This is a private hackathon open to UmojaHack Senegal participants. If you are a university student in Senegal and would like to participate, contact Thierno Ibrahima Diop.
Expresso is an African telecommunications company that provides customers with airtime and mobile data bundles. The objective of this challenge is to develop a machine learning model to predict the likelihood of each Expresso customer “churning,” i.e. becoming inactive and not making any transactions for 90 days.
This solution will help Expresso to better serve their customers by understanding which customers are at risk of leaving. CLICK HERE FOR MORE ...
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Go on UmojaHack page to download all CSV files of dataset and put files into folder DATASET/CSV/ ;
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Go into folder NOTEBOOKS/ and execute all cells of the notebook cat_starter_customer_churn.ipynb ;
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Go into folder SUBMISSIONS/, get the created submission file vanilla_cat_no_fillna_seed=xxx_n-sfk=zzz_score=yyy.csv and submit the submission file to Zindi platform.
|----DATASET
| |--- CSV
| |--- << Put all CSV files provided for challenge here >>
|
|----NOTEBOOKS
| |--- cat_starter_customer_churn.ipynb
|
|----SUBMISSIONS
| |--- << vanilla_cat_no_fillna_seed=xxx_n-sfk=zzz_score=yyy.csv >>
|
|---- .gitignore
|---- Readme.md
🏅Position: 1st / 67
🏅Score: 0.250550624111933 (LogLoss)
Name | Zindi ID | Github ID |
---|---|---|
Muhamed TUO | @Nazario😁 | @NazarioR9 |
Cédric MANOUAN | @Zeus😆 | @dric2018 |
Emmanuel KOUPOH | @eaedk😂 | @eaedk |
MIT License
<<<<<<< HEAD
Copyright (c) 2020 Emmanuel KOUPOH for TheCIA team.
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## Final Leaderboard
>>>>>>> 23c9dbce4e880024d23d8a776913ea4b51727263
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