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Comment by jorgemf | Hacker News Reader

I would like to use it but I think the price doesn't justify the tool. For a team of 5 people github is $25 a month, you are $745 a month. I do understand a price a bit higher that github but not 30 times more expensive.

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I like, that the price is so high. That makes it a least seem to be a sustainable business. And when you pay your ML people 10k a month, the $25 is less than the coffee they will drink in the office.

145 per user per month, not 25. Not all countries pay 10k a month to their employees

Thanks @jorgemf. Keep in mind that $745 also includes unlimited usage of our hyper-parameter optimization service.

Is hyper-parameter optimization a cherry on top or one of the core value propositions?

IME hyper-parameter optimization doesn't require much in terms of implementation effort (e.g. [1]), but requires compute. I would be surprised if a professional ML/DS user were to seriously consider paying for the implementation of the optimization.

[1] https://people.eecs.berkeley.edu/~kjamieson/hyperband.html

Are there any similarities or distinctions between this article (link below) and how your system works to tune hyper-parameters?

https://blog.coast.ai/lets-evolve-a-neural-network-with-a-ge...

This article seems to discuss genetic algorithms which could be used for hyperparam optimization. We use another method called Bayesian (GP) hyperparam optimization. According to our internal benchmarks and academic research Bayesian methods outperform genetic algorithms. Another thing to keep in mind that we automate the entire process for you. You only need to provide a list of parameters you'd like to tune.

That service doesn't justify the price tag for me.

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