Show HN: Machine learning automation from creating to using models in production

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  • igel

    a delightful machine learning tool that allows you to train, test, and use models without writing code

    Thanks for the feedback! When I first started the project, it was not thought for production. Just for fast prototyping and experimenting with no efforts at all. However, users liked the tool and started requesting more features including support for serving models and eventually deploying (e.g this issue https://github.com/nidhaloff/igel/issues/62)

    I agree with your point of vue. However, igel is fairly new and evolving fast. Using igel to serve trained model is a new feature that was implemented in the new release so igel has a long way to go in order to be a solid product for production use.It will surely get more mature with time.

    Finally, notice that I didn't recommend running it in production. Just mentioned that it is possible and takes no efforts at all. However, if the user generated a trained model then anything can be done with it from there. Technically, the user can implement his/her own server and use the model as wanted. Obviously, users should do that if they want more control ;)

  • SimpleML

    Machine learning that just works, for effortless production applications

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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