Learn to generate synthetic tabular data using a conditional generative adversarial network (GAN).

Photo by Hayden Dunsel on Unsplash


In the previous article, we introduced the concept of synthetic data and its applications in data privacy and machine learning. In this article, we will show you how to generate synthetic tabular data using a generative adversarial network (GAN).

Tabular data is one of the most common and important data…

Machine Learning Pipelines

Machine Learning (ML) pipelines help to automate the ML life cycle, streamline the workflow, and unlock faster iteration of models from development to deployment. Pipelines also allow data, models and experiments to be more easily tracked, and monitored. …

How synthetic data can be used for data privacy protection and machine learning model development.


“Data is the new oil in the digital era”¹. Software engineers and data scientists often need access to large volumes of real data to develop, experiment, and innovate. Collecting such data unfortunately also introduces security liabilities and privacy concerns which affect individuals, organizations, and society at large. …

Lulu Tan

Machine Learning Engineer @ Unity — linkedin.com/in/lulutan-lt/

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