https://github.com/codesandtags/fraud-predictive-model
An example to have a fraud predictive model in real time using Machine Learning
https://github.com/codesandtags/fraud-predictive-model
Last synced: about 2 months ago
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An example to have a fraud predictive model in real time using Machine Learning
- Host: GitHub
- URL: https://github.com/codesandtags/fraud-predictive-model
- Owner: codesandtags
- Created: 2023-06-01T23:32:45.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-06-14T02:59:54.000Z (about 3 years ago)
- Last Synced: 2025-03-13T09:39:03.357Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 7.12 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Fraud Model
A fraud model to detect fraudulent credit card transactions.
## Problem Definition
## Data
## Evaluation
- Find patterns
- Transactions with most fraud patterns
## Features
## Modelling
## Experimentation
## Environemnt Setup
To install the environment for this project, run the following command:
```sh
conda create --prefix ./env pandas numpy matplotlib scikit-learn jupyter
```
To activate the environment, run the following command:
```sh
conda activate ./env
```
To deactivate the current environment, run the following command:
```sh
conda deactivate
```
To check the current environment, run the following command:
```sh
conda info --envs
```
To export the dependencies of the environment, run the following command:
```sh
conda env export > environment.yml
```
To create the environment from a environment.yml file, run the following command:
```sh
conda env create -f environment.yml
```