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For Problem type , select Classification. In the following example, we drop the columns Timestamp, Country, state, and comments, because these features will have least impact for classification of our model. For Training method , select Auto. This instance configuration is sufficient for the demo. Choose Create.
” – James Tu, Research Scientist at Waabi Play with this project live For more: Dive into documentation Get in touch if you’d like to go through a custom demo with your team Comet ML Comet ML is a cloud-based experiment tracking and optimization platform.
Simulation of consumption of queue up to drivers estimated position becomes an easy simple algorithm and results in wait time classification. Google built a no-code end to end ML based framework called Visual blocks and published a post on this. They refer to this as our “demand” model.
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