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https://github.com/DeutscheAktuarvereinigung/Data_Science_Challenge_2020_Betrugserkennung
In this notebook we take a look at a relevant project that is frequently encountered by insurers: Fraud Detection. For this purpose we use a car data set from a public source and will show the necessary steps to establish an automated fraud detection.
https://github.com/DeutscheAktuarvereinigung/Data_Science_Challenge_2020_Betrugserkennung
actuarial-modeling betrugserkennung challenge data-science datasciencechallenge fraud-detection frauddetection
Last synced: 3 months ago
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In this notebook we take a look at a relevant project that is frequently encountered by insurers: Fraud Detection. For this purpose we use a car data set from a public source and will show the necessary steps to establish an automated fraud detection.
- Host: GitHub
- URL: https://github.com/DeutscheAktuarvereinigung/Data_Science_Challenge_2020_Betrugserkennung
- Owner: DeutscheAktuarvereinigung
- License: gpl-3.0
- Created: 2020-11-16T16:35:47.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2020-11-17T14:04:57.000Z (almost 4 years ago)
- Last Synced: 2024-07-29T19:28:01.582Z (4 months ago)
- Topics: actuarial-modeling, betrugserkennung, challenge, data-science, datasciencechallenge, fraud-detection, frauddetection
- Language: Jupyter Notebook
- Homepage:
- Size: 11.5 MB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 0
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- jimsghstars - DeutscheAktuarvereinigung/Data_Science_Challenge_2020_Betrugserkennung - In this notebook we take a look at a relevant project that is frequently encountered by insurers: Fraud Detection. For this purpose we use a car data set from a public source and will show the necessa (Jupyter Notebook)