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GitHub / abdoghareeb46 / NTI-Final-Assignment

NTI-Final-Assignment Use flask(python) and shiny dashboard (R) to build simple user interface to see how choosing classification model may affect prediction accuracy, using Customer Churn Dataset.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abdoghareeb46%2FNTI-Final-Assignment
PURL: pkg:github/abdoghareeb46/NTI-Final-Assignment

Stars: 2
Forks: 0
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 534 KB
Dependencies parsed at: Pending

Created at: over 6 years ago
Updated at: over 1 year ago
Pushed at: over 6 years ago
Last synced at: over 1 year ago

Topics: classification-algorithims, data-analysis, data-science, flask-api, imbalanced-data, jupyter-notebook, machine-learning, machine-learning-algorithms, oversampling, prediction-algorithm, python, r, randomoversampler, shinydashboard, smote

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