nidhaloff / igel
I'm also working on a GUI desktop app for igel based on people's requests. You can find it under Igel-UI. Please consider supporting the project!
I needed a tool sometimes, which I can use to fast create a machine learning prototype. Whether to build some proof of concept or create a fast draft model to prove a point. I find myself often stuck at writing boilerplate code and/or thinking too much of how to start this.
Therefore, I decided to create igel. Hopefully, it will make it easier for technical and non-technical users to build machine learning models.
Igel supports all sklearn's machine learning functionality, whether regression, classification or clustering. Precisely, you can use 63 different machine learning model in igel.
Igel supports most used dataset types in the data science field. For instance, your input dataset can be a csv, txt, excel sheet, json or even html file that you want to fetch. All these types are supported by igel. In the background, igel uses pandas to read and convert your input dataset to a dataframe.
And then running it and attaching your current directory (does not need to be the igel directory) as /data (the workdir) inside of the container:
