GitiHubi/deepAI
Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.
This project helps financial professionals identify unusual or potentially fraudulent patterns in large sets of accounting data. It takes your raw accounting transaction data and uses an advanced neural network to highlight anomalies that might otherwise go unnoticed. This is ideal for auditors, forensic accountants, or financial compliance officers looking to enhance their anomaly detection capabilities.
210 stars. No commits in the last 6 months.
Use this if you need to detect unusual transactions or potential fraud within large volumes of accounting or financial statement data.
Not ideal if you are looking for a plug-and-play software solution and do not have technical expertise with Python and machine learning.
Stars
210
Forks
89
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Aug 07, 2019
Commits (30d)
0
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