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Fastag Fraud Detection System
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abhisheks008 authored Jul 6, 2024
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8 changes: 8 additions & 0 deletions Fastag Fraud Detection System/Dataset/README.MD
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# Dataset
## Overview
This folder contains the dataset used for the Fast Tag Fraud Detection project.

- **File**: `dataset.csv`
- **Description**: This CSV file includes Fastag transaction data, detailing various attributes such as vehicle type, toll booth location, transaction amount, etc.

If the dataset is too large to upload here, please refer to the [link](https://www.kaggle.com/datasets/krishujeniya/fastag-frauds-records) to download it.
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21 changes: 21 additions & 0 deletions Fastag Fraud Detection System/Images/README.MD
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# Images

## Overview
This folder contains images generated during different stages of the project:

## Structure
- `.eda` : Visualizations from exploratory data analysis.


- `.explanatory_analysis`: Detailed charts explaining relationships and patterns.


- `.feature_engineering`: Visuals created during feature engineering.


- `.ml_deployment`: Images related to the model deployment.


- `.ml_evaluation`: Actual vs predicted graphs and other evaluation metrics.
- `.Actual_vs_Predicted`: Comparison between actual and predicted values.

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21 changes: 21 additions & 0 deletions Fastag Fraud Detection System/Model/README.MD
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# Model

This folder contains the Jupyter notebook and associated files for the project.

## Contents
- **File**: `projectfile.ipynb`
- Contains all the steps of data exploration, feature engineering, model development, and evaluation.

- **File**: `dataset.csv`
- The dataset used within the notebook for analysis and model training.


- **File**: `model.pkl`
- The trained model saved in a pickle file format.
- Use this model for deployment or further analysis.
- Load the model using the following code:


## Instructions
1. Open the `projectfile.ipynb` to view the step-by-step workflow.
2. Install the necessary dependencies listed in the `requirements.txt` file.
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