https://github.com/ayushexel/frauddetectionieee

https://github.com/ayushexel/frauddetectionieee

kaggle machine-learning sklearn

Last synced: 7 months ago
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• Host: GitHub
• URL: https://github.com/ayushexel/frauddetectionieee
• Owner: AyushExel
• Created: 2020-03-27T17:58:54.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-03-27T18:15:59.000Z (over 5 years ago)
• Last Synced: 2025-02-08T09:38:22.395Z (9 months ago)
• Topics: kaggle, machine-learning, sklearn
• Language: Jupyter Notebook
• Size: 613 KB
• Stars: 2
• Watchers: 3
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# IEEE-cis-fraud-detection

In this tutorial, we’ll see how the wandb’s direct integration with scikit-learn enables you to visualize all the details about the model, data and the performance metrics on your wandb dashboard by using a single line of code.

The datasets that we’ll be using is IEE-CIS-Fraud Detection. The dataset is available on Kaggle. We’ll build our code on top of an approach already available on github.

Let’s have a look at the dataset.

This repository contains solutions to the [IEEE-CIS Fraud Detection](https://www.kaggle.com/c/ieee-fraud-detection)

# Visualizations Generated using WandB

![](https://github.com/AyushExel/FraudDetectionIEEE/blob/master/visualizations/Screenshot%20from%202020-03-27%2021-53-46.png)

![](https://github.com/AyushExel/FraudDetectionIEEE/blob/master/visualizations/Screenshot%20from%202020-03-27%2022-00-04.png)

![](https://github.com/AyushExel/FraudDetectionIEEE/blob/master/visualizations/Screenshot%20from%202020-03-27%2022-12-43.png)

![](https://github.com/AyushExel/FraudDetectionIEEE/blob/master/visualizations/Screenshot%20from%202020-03-27%2022-17-42.png)

![](https://github.com/AyushExel/FraudDetectionIEEE/blob/master/visualizations/Screenshot%20from%202020-03-27%2022-21-13.png)

![](https://github.com/AyushExel/FraudDetectionIEEE/blob/master/visualizations/Screenshot%20from%202020-03-27%2022-33-35.png)