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A delightful machine learning tool that allows you to train/fit, test, and use models without writing code. The goal of the project is to provide machine learning for everyone, both technical and non-technical users. I sometimes needed a tool sometimes, which I could use to fast create a machine learning prototype. Whether to build some proof of concept, create a fast draft model to prove a point or use auto ML. I find myself often stuck writing boilerplate code and thinking too much about where to start. Therefore, I decided to create this tool. igel is built on top of other ML frameworks. It provides a simple way to use machine learning without writing a single line of code. Igel is highly customizable, but only if you want to. Igel does not force you to customize anything. Besides default values, igel can use auto-ml features to figure out a model that can work great with your data.
Features
- Supports most dataset types (csv, txt, excel, json, html) even just raw data stored in folders
- Supports all state of the art machine learning models (even preview models)
- Provides flexibility and data control while writing configurations
- Supports different data preprocessing methods
- Supports both hyperparameter search (version >= 0.2.8)
- Supports different sklearn metrics for regression, classification and clustering
- Supports multi-output/multi-target regression and classification
- Supports multi-processing for parallel model construction
Project Samples
