Synthetic-Data-Artist AmirhosseinHonardoust · COMPLETED
A professional, research-grade comparison of Gaussian Copula and Variational Autoencoder (VAE) methods for synthetic tabular data generation. Includes full evaluation pipeline with distribution overlap, correlation analysis, PCA projections, pairplots, metrics, and automated visual reports.
github.com/AmirhosseinHonardoust/Synthetic-Data-Artist · ★ 21 · Forks 0 · Size 2.2 MB
SUMMARY
Technologies 9
Scored 9
Observed 9
Practices 6
Evidence 11
Skips 0
COVERAGE
Analyzed 42 files · 61 commits · 0 API calls
TECHNOLOGIES & DEPTH
JSON LANGUAGE Depth 70
2 files · PRODUCTION
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
21 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 78
11 files · PRODUCTION, TEST
pandas LIBRARY Depth 78
13 files · PRODUCTION, TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-11-10
Last commit 2026-08-12
Active months 3
Commits 61