scienxlab/redflag

Safety net for machine learning pipelines. Plays nice with sklearn and pandas.

47
/ 100
Emerging

Building a machine learning model often involves cleaning and preparing your data. This tool acts as an automatic safety net, flagging potential issues in your datasets (like imbalanced categories, unusual values, or data leakage) before they lead to poor model performance. It takes your raw data (features and targets) and alerts you to common pitfalls, helping data scientists and machine learning engineers build more robust models.

No commits in the last 6 months. Available on PyPI.

Use this if you want an automated system to detect common data quality issues and potential problems in your machine learning datasets before training your models.

Not ideal if you need a visual-first data exploration and profiling tool, or if you are looking for a system to monitor model performance after deployment.

data-quality machine-learning-engineering predictive-modeling data-science-workflow model-development
Stale 6m
Maintenance 0 / 25
Adoption 6 / 25
Maturity 25 / 25
Community 16 / 25

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Stars

21

Forks

6

Language

Python

License

Apache-2.0

Last pushed

Apr 22, 2024

Commits (30d)

0

Dependencies

3

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