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Detect fraudulent credit card transactions using various classification Machine Learning Models with unbalanced data

Python 0.11% Makefile 0.18% Jupyter Notebook 99.70%

credicardfrauddetection's Introduction

Data analysis

  • Document here the project: CrediCardFraudDetection
  • Description: Project Description
  • Data Source:
  • Type of analysis:

Please document the project the better you can.

Startup the project

The initial setup.

Create virtualenv and install the project:

sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv ~/venv ; source ~/venv/bin/activate ;\
    pip install pip -U; pip install -r requirements.txt

Unittest test:

make clean install test

Check for CrediCardFraudDetection in gitlab.com/{group}. If your project is not set please add it:

  • Create a new project on gitlab.com/{group}/CrediCardFraudDetection
  • Then populate it:
##   e.g. if group is "{group}" and project_name is "CrediCardFraudDetection"
git remote add origin [email protected]:{group}/CrediCardFraudDetection.git
git push -u origin master
git push -u origin --tags

Functionnal test with a script:

cd
mkdir tmp
cd tmp
CrediCardFraudDetection-run

Install

Go to https://github.com/{group}/CrediCardFraudDetection to see the project, manage issues, setup you ssh public key, ...

Create a python3 virtualenv and activate it:

sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv -ppython3 ~/venv ; source ~/venv/bin/activate

Clone the project and install it:

git clone [email protected]:{group}/CrediCardFraudDetection.git
cd CrediCardFraudDetection
pip install -r requirements.txt
make clean install test                # install and test

Functionnal test with a script:

cd
mkdir tmp
cd tmp
CrediCardFraudDetection-run

credicardfrauddetection's People

Contributors

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Watchers

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