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DataTransform_Training
DataTransform_Training
 
 
DataTransformation_Prediction
DataTransformation_Prediction
 
 
DataTypeValidation_Insertion_Prediction
DataTypeValidation_Insertion_Prediction
 
 
DataTypeValidation_Insertion_Training
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EDA
EDA
 
 
PredictionArchivedBadData
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Prediction_Batch_files
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Prediction_Database
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Prediction_FileFromDB
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Prediction_Logs
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Prediction_Output_File
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Prediction_Raw_Data_Validation
Prediction_Raw_Data_Validation
 
 
Prediction_Raw_Files_Validated
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TrainingArchiveBadData
TrainingArchiveBadData
 
 
Training_Batch_Files
Training_Batch_Files
 
 
Training_Database
Training_Database
 
 
Training_FileFromDB
Training_FileFromDB
 
 
Training_Logs
Training_Logs
 
 
Training_Raw_data_validation
Training_Raw_data_validation
 
 
__pycache__
__pycache__
 
 
application_logging
application_logging
 
 
best_model_finder
best_model_finder
 
 
data
data
 
 
data_ingestion
data_ingestion
 
 
data_preprocessing
data_preprocessing
 
 
documentation
documentation
 
 
file_operations
file_operations
 
 
models
models
 
 
preprocessing_data
preprocessing_data
 
 
templates
templates
 
 
Procfile
Procfile
 
 
README.md
README.md
 
 
default of credit card clients.xls
default of credit card clients.xls
 
 
main.py
main.py
 
 
predictFromModel.py
predictFromModel.py
 
 
prediction_Validation_Insertion.py
prediction_Validation_Insertion.py
 
 
requirements.txt
requirements.txt
 
 
schema_prediction.json
schema_prediction.json
 
 
schema_training.json
schema_training.json
 
 
test.py
test.py
 
 
trainingModel.py
trainingModel.py
 
 
training_Validation_Insertion.py
training_Validation_Insertion.py
 
 

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Card-Fraud-Detection

  • Problem Statement

  • To build a classification methodology to determine whether a person defaults(whether he / she would be able to pay the debt on time or not) the credit card payment for the next month.

  • Run the requirements.txt file

  • pip install -r requirements.txt

  • Read the documentation folder -creditCardDefaulters.docx

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