A tool to generate synthetic dataset of corporate travels
-
Updated
Jul 3, 2020 - Jupyter Notebook
A tool to generate synthetic dataset of corporate travels
This project utilizes Generative Adversarial Networks (GANs) to tackle the problem of credit card fraud detection. GANs are a powerful deep learning technique that can be used for generating synthetic data, which can be beneficial in situations with imbalanced datasets, such as fraud detection.
JR (jrnd.io) Source Connector for Apache Kafka Connect
An add-on for Blender that allows you to generate and render three-dimensional scenes that can be automatically annotated and used for training neural networks.
Implementation of BISECT from [2] for Hidden Outlier generation.
Add a description, image, and links to the syntetic-dataset topic page so that developers can more easily learn about it.
To associate your repository with the syntetic-dataset topic, visit your repo's landing page and select "manage topics."