What are the benefits of having ML in JavaScript I.e. the deeplearn.js (now tensorflow) stuff, as opposed to implementing the ML steps in a python backend?

closed as primarily opinion-based by Stephen Rauch, wacax, Aditya, timleathart, Toros91 Apr 6 at 1:09

Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center, please edit the question.

  • If run on the front-end, you can offload training, and give the user a say; useful when subjectivity is involved. – Emre Apr 2 at 16:16
up vote 2 down vote accepted

There are a lot of services that offer free or very cheap hosting of static websites. If you are able to implement your ML model in JS this allows you to deploy your product/app/whatever easily and with low cost. In comparison, requiring a backend server running your model is harder to setup and maintain, in addition to costing more.

JavaScript is very a popular language, especially for web developers. Machine learning in a web-native language allows additional programmers to use machine learning more easily.

JavaScript is a client-side language that allows deep learning models to predict without server-side resources.

It is a bit technical and depends where you use your JavaScript code. It is used in both backend and frontend apps. My opinion is that using that in frontend apps can help your ML algorithms run on distributed devices. Take a look at here. You can use this language to run ML codes on hosts' computers.

Not the answer you're looking for? Browse other questions tagged or ask your own question.