Under project templates - coming soon they say it will work with tabular data.

I expect, as they allude to, it will begin with simple classification tasks in order to stick with the clean user experience they've built. But I'm super eager to see what they propose in this area.

We are working on adding more project templates in the future, and Lobe is designed upon the idea that machine learning should be made easy—no matter the problem type you are facing.

CreateML (https://developer.apple.com/machine-learning/create-ml) if you have MacOs, can handle tabular data.

I'm the founder, but you can use sysrev.com to review pdfs, json, text, etc. and assign labels / do annotations. You can see https://blog.sysrev.com/simple-ner/ for how to build something like a gene named entity recognizer in text. We have mechanical turk like compensation tools too, but you'll need to ping me (tom@insilica.co) for access.

There are other options for this too, I think spacy.io has an annotation app.

Clarifai does images + text (https://www.clarifai.com/).

Yep we are starting with image classification for this initial beta launch, but plan to expand to more data types and problem types in future releases! The vision is to make a tool usable by anyone to build custom machine learning

Check out Monument (https://www.monument.ai) (shameless plug)

We specialize in tabular data and are building a pipeline-based approach for creating and serving models.