Source: towardsdatascience.com

Where Should You Deploy Your Model?
You’ve gone through the effort in cleaning your data. You are finally ready to put this model into production, but the overwhelming amount of options you have to deploy your model with is overwhelming. Although we are very fortunate to live in an era where cloud computing has taken a large domain in the machine-learning market, this also has a draw-back in that all of the options can often make it difficult to narrow your decision down to which one is going to best suite your model and your personal situation.

If it isn’t possible for you to make your money back on the computation, then it likely isn’t worth hosting in the first place.

Another problem with a Heroku app is that it is embedded into the Heroku system by default, which gives you very little flexibility to add anything or expand your services in the future.

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