tirthajyoti/Synthetic-data-gen
Various methods for generating synthetic data for data science and ML
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.
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83
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42
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Aug 15, 2021
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