jeongyoonlee/Kaggler

Code for Kaggle Data Science Competitions

60
/ 100
Established

This project provides tools for preparing your data and building machine learning models efficiently. It takes in raw datasets, helps you clean and transform them, and then outputs predictions or insights. It's designed for data scientists and analysts who want to quickly experiment with different modeling approaches, especially for classification or regression tasks.

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

Use this if you are a data scientist or analyst looking to quickly prototype and iterate on machine learning models, especially when dealing with categorical features or online learning scenarios.

Not ideal if you need a comprehensive, low-code AutoML solution for non-technical users or are working exclusively with deep learning architectures for complex data types like images or natural language.

data-preprocessing predictive-modeling feature-engineering machine-learning-prototyping model-ensemble
Stale 6m No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 25 / 25

How are scores calculated?

Stars

750

Forks

167

Language

Python

License

MIT

Last pushed

Apr 25, 2024

Commits (30d)

0

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