CTGAN: Generate high-quality, realistic tabular data using GAN-based models for diverse machine learning applications and analyses..DoppelGANger: Create accurate time-series data through GANs, ideal for AI research, simulations, and predictive modeling tasks..Synner: Produce customized synthetic datasets specifically designed for testing applications, algorithms, and performance evaluation scenarios..Synthea: Simulate comprehensive synthetic healthcare data, useful for public health studies and innovative medical research projects..SDV: Generate varied datasets employing Statistical Data Modeling techniques for multiple domains, enhancing analysis and insights..Read More Stories
CTGAN: Generate high-quality, realistic tabular data using GAN-based models for diverse machine learning applications and analyses..DoppelGANger: Create accurate time-series data through GANs, ideal for AI research, simulations, and predictive modeling tasks..Synner: Produce customized synthetic datasets specifically designed for testing applications, algorithms, and performance evaluation scenarios..Synthea: Simulate comprehensive synthetic healthcare data, useful for public health studies and innovative medical research projects..SDV: Generate varied datasets employing Statistical Data Modeling techniques for multiple domains, enhancing analysis and insights..Read More Stories