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fgibarra/fraud-prevention

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App README

Final project of bootcamp EDVai 2023

Description

This is the final project of the bootcamp EDVai 2023.

The project is divide in several parts:

  • —notebooks: contains the notebooks used to data exploration, data cleaning, data analysis and model creation.
  • —api: contains the code of the api. The api is used to predict frauds. This code is realized with FastAPI.
  • —app: contains the code of the web application realized with Gradio.

Other files:

  • —data: contains the data used in the project.
  • —model: contains the models used in the project.
  • —docs: contains the documentation of the project.

Installation

To install the project, you need to clone the repository and install the requirements. The requirements are in the three files: notebooksrequirements.txt, apirequirements.txt and app_requirements.txt.

Depends on you the part of the project you want to use, you need to install the requirements of the part.

bash
python -m venv venv
pip install -r notebooks_requirements.txt
pip install -r api_requirements.txt
pip install -r app_requirements.txt

Usage

If you want to use the notebooks, you need to run the notebooks in the following order:

  • —01__Adaptacion.ipynb
  • —02__Correlacion.ipynb
  • —03__Preparacion.ipynb
  • —04__Clustering.ipynb
  • —05__Modelo.ipynb

If you want to use the api, you need to run the following command:

bash
python main.py

If you want to use the app, you need to run the following command:

bash
python app.py

Deploy