tirthajyoti/Synthetic-data-gen

Various methods for generating synthetic data for data science and ML

46
/ 100
Emerging

This project helps data scientists and machine learning practitioners generate diverse datasets for training and testing algorithms. It takes your specifications for data characteristics—like the number of samples, features, statistical distributions, and desired complexity—and outputs synthetic datasets tailored for classification, regression, clustering, or time series problems. This is ideal for those learning new algorithms or needing to explore algorithm behavior under specific, controlled data conditions.

No commits in the last 6 months.

Use this if you need custom, flexible datasets to rigorously test and understand the intricacies of machine learning algorithms, without the effort of finding and cleaning real-world data.

Not ideal if your primary goal is to gain experience with the full lifecycle of real-world data collection, cleaning, and exploratory analysis.

machine-learning-education algorithm-testing data-simulation model-training statistical-modeling
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 21 / 25

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Stars

83

Forks

42

Language

Jupyter Notebook

License

MIT

Last pushed

Aug 15, 2021

Commits (30d)

0

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