[ojosilva]

We're using NodeJS for data science with Tensorflow JS and it's excellent, at least for our use case, which is 90% discrete data, mostly classification tasks.

NodeJS evented architecture is great for multitasking training (and prediction) jobs. I use Node Streams to extract and process data flows out of several data sources on my Macbook Air M1 using the new Neural Engine 16-core chip to train CNN models with excellent results.

Data prediction then runs on a ReactJS app, which gives my users a way to model, transform and visualize data on a browser. Everything is in Typescript, which reduces cognitive overload for our programmers and produces good end-to-end duck-type coherence and easy, integrated testing.

Now, most data science libs for Javascript are either on their infancy, are proof-of-concept or just abandoned, but TFJS is solid and if you know what, why and to which extent you're using JS for data science, then it's absolutely fine.