4 ms·
From what I could see, the dataset has 300 data points (and less than 100 attributes/features), so it should take less than a minute to train a state of the art
by levesque 4y ago
From what I could see, the dataset has 300 data points (and less than 100 attributes/features), so it should take less than a minute to train a state of the art model on a normal computer. Cost: 0$
- monkeydust 4y agoRight, it's a small dataset no GPU, guess your paying for aws software but I think there are plenty of open source equivalents that could match/beat these results with similar level of effort.
- petra 4y agoAny affordable(for a small business) no-code/low-code ML for small business?
- blackbear_ 4y agoThis one perhaps [1]? I only tried it for ten minutes but it seemed nice. [1] https://github.com/biolab/orange3 https://github.com/biolab/orange3
- moffkalast 4y agoAh Orange, that takes me back to university days. What a pain that thing was to work with.
- levesque 4y agoNo joke, it was the clunkiest library ever. I wonder if they ended up improving it.
- spywaregorilla 4y agoTraining an ML model is very easy. You can learn to pass things through an sklearn decision tree model over a couple hours. Interpreting it is a more battle hardened task. Don't blindly trust such tools.
- jhfdbkofdchk 4y agoKNIME is a free, fairly well used tool in some sectors, for doing low and no-code analysis and machine learning models. https://en.wikipedia.org/wiki/KNIME https://en.wikipedia.org/wiki/KNIME