nidhaloff/igel
A no-code machine learning CLI tool that wraps scikit-learn and other frameworks for model training, testing, and deployment.
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Igel provides a command-line interface for machine learning workflows, allowing users to train, evaluate, and use models through configuration files rather than code. It wraps scikit-learn and other ML libraries under the hood, supporting common algorithms, preprocessing, and AutoML capabilities. Users define model parameters and data paths in YAML, JSON, or via CLI arguments, and the tool handles the rest.
Frequently asked
- What is nidhaloff/igel?
- A no-code machine learning CLI tool that wraps scikit-learn and other frameworks for model training, testing, and deployment.
- Is igel open source?
- Yes — nidhaloff/igel is open source, released under the MIT license.
- What language is igel written in?
- nidhaloff/igel is primarily written in Python.
- How popular is igel?
- nidhaloff/igel has 3.1k stars on GitHub.
- Where can I find igel?
- nidhaloff/igel is on GitHub at https://github.com/nidhaloff/igel.