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carpentries-incubator / ml4bio-workshop

Materials for a workshop introducing machine learning to biologists
https://carpentries-incubator.github.io/ml4bio-workshop/
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Related projects with graphical interfaces #32

Open agitter opened 5 years ago

agitter commented 5 years ago
agitter commented 5 years ago

Microsoft has drag and drop machine learning interfaces, described here:

agitter commented 5 years ago

Turi Create doesn't seem to have a graphical interface, but it was recommended to me by a machine learning novice. This could be a potential resource for someone who can write Python code and wants more wrappers and assistance than scikit-learn provides.

agitter commented 5 years ago

DataChat: https://datachat.ai/

agitter commented 5 years ago

A good summer exercise may be to spend a little time with each of these tools to see whether we would recommend them to participants once they have learned basic ML concepts.

cmilica commented 5 years ago

anaconda just released Voilà - according to the one line summary

Voilà turns Jupyter notebooks into standalone web applications.

Here are the links https://blog.jupyter.org/and-voil%C3%A0-f6a2c08a4a93 and https://anaconda.org/conda-forge/voila

agitter commented 5 years ago

I looked at Voilà briefly, and my first impression is that this is different from Binder because it strips away all of the code and displays only the output of code cells. That output can include interactive plots and widgets, creating a simple interactive interface for users who do not want to see the code. The example also looks like it is running locally (as opposed to Binder running the notebook remotely), but I didn't check carefully.

Voilà could be appealing for our demo notebook. It would be an intermediate layer between the ml4bio GUI and the full notebook with scikit-learn code.

If Voilà runs locally, we would still need users to configure a conda environment on their machine. One appealing aspect of Binder and similar services is they do not have any local dependencies.

cmilica commented 5 years ago

Yes, it looks like it runs locally.

Makes sense! I will play around with some of these this week.

agitter commented 4 years ago

@cmilica found https://www.streamlit.io/ It builds interactive machine learning apps with compact Python scripts. The gallery has lots of cool examples.

agitter commented 4 years ago

Milica has also been looking into interactive visualizations that teach machine learning concepts, such as https://thomas-tanay.github.io/post--L2-regularization/

agitter commented 4 years ago

Galaxy-ML is a relevant resource:

agitter commented 4 years ago

Gradio generates GUIs for machine learning models

agitter commented 3 years ago

PennAI has a graphical interface and supports AutoML:

The interface supports saving a trained model and exporting a script to reproduce the results, which we've discussed.

cmilica commented 3 years ago

Thought this was really cool https://climateprimer.mit.edu/

agitter commented 3 years ago

@cmilica found http://www.r2d3.us/ with great visualizations for decision trees and bias-variance tradeoffs.