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GitHub / RohitMacherla3 / customer-churn-prediction
This project aims to aims to predict the customer churn (likelihood of a customer leaving the company) for a telecom company using a variety of ML classification algorithms.
Stars: 0
Forks: 1
Open Issues: 0
License: mit
Language: Jupyter Notebook
Repo Size: 7.4 MB
Dependencies:
54
Created: about 2 months ago
Updated: about 1 month ago
Last pushed: about 1 month ago
Last synced: about 1 month ago
Topics: classification-algorithm, customer-churn-analysis, customer-churn-prediction, eda, feature-engineering, gridsearchcv, hyperparameter-tuning, machine-learning, python
Files
Dependencies
- GitPython ==3.1.43
- Jinja2 ==3.1.3
- MarkupSafe ==2.1.5
- Pygments ==2.17.2
- altair ==5.3.0
- attrs ==23.2.0
- blinker ==1.7.0
- cachetools ==5.3.3
- certifi ==2024.2.2
- charset-normalizer ==3.3.2
- click ==8.1.7
- contourpy ==1.2.1
- cycler ==0.12.1
- fonttools ==4.50.0
- gitdb ==4.0.11
- idna ==3.6
- imbalanced-learn ==0.12.2
- imblearn ==0.0
- joblib ==1.3.2
- jsonschema ==4.21.1
- jsonschema-specifications ==2023.12.1
- kiwisolver ==1.4.5
- markdown-it-py ==3.0.0
- matplotlib ==3.8.4
- mdurl ==0.1.2
- numpy ==1.26.4
- packaging ==24.0
- pandas ==2.2.1
- pillow ==10.3.0
- protobuf ==4.25.3
- pyarrow ==15.0.2
- pydeck ==0.8.1b0
- pyparsing ==3.1.2
- python-dateutil ==2.9.0.post0
- pytz ==2024.1
- referencing ==0.34.0
- requests ==2.31.0
- rich ==13.7.1
- rpds-py ==0.18.0
- scikit-learn ==1.4.1.post1
- scipy ==1.13.0
- seaborn ==0.13.2
- six ==1.16.0
- smmap ==5.0.1
- streamlit ==1.33.0
- tenacity ==8.2.3
- threadpoolctl ==3.4.0
- toml ==0.10.2
- toolz ==0.12.1
- tornado ==6.4
- typing_extensions ==4.10.0
- tzdata ==2024.1
- urllib3 ==2.2.1
- xgboost ==2.0.3