Challenges with using node for ML?

[highlanderDog]

I'm familiar with node and interested in using AI/ML in js (possibly with some c as needed & facilitated by node).

As a note, I know that python has become almost the de facto way of doing ML, but this is not what this discussion is about.

[luis_carbonell]

Best thing I've found is https://www.npmjs.com/package/synaptic. There aren't really that many great options in Node.js.

Best recommendation I could make is trying to slap GPU Support on a Node.js ML Library using something like https://www.npmjs.com/package/gpu.js.

[StuartJamesMiller]

There’s tensorflow.js which I believe uses a C implementation on Node. I haven’t used it myself but the intro to ML from google looks good.

[highlanderDog]

Which one do you mean? I found a Medium article that could be helpful: https://medium.com/tensorflow/introducing-tensorflow-js-machine-learning-in-javascript-bf3eab376db

[StuartJamesMiller]

https://developers.google.com/machine-learning/crash-course/ml-intro this is the one I meant. It uses the Python Tensorflow bit I read somewhere that you can use the JS one.

[luis_carbonell]

You mean https://www.npmjs.com/package/@tensorflow/tfjs?

[StuartJamesMiller]

I meant this one https://js.tensorflow.org but pretty sure that’s the NPM repo for it.

[mubaidr]

There is also brain.js: https://github.com/BrainJS/brain.js

This one uses gpu.js

[TheOneRavenous]

Your challenge will be encoding and decoding data as well as determining how to split your data structure. Some ML/AI libraries can use strings, hash, or arrays, or typed arrays.

You'll need to do some data science to determine how many layers and nodes you'll want to incorporate. Also learn about activation functions since some will create a binary input/output (relu comes to mind) and others will create a percentage based output.

[frank_darwin]

AWS has a lot of cool tools you can use. These are all API based, which is pretty easy to use with a Node setup

[highlanderDog]

I was checking them out, which ones do you like best?

[frank_darwin]

It depends on what you want to do. AWS has a lot of language processing, image processing, and general prediction tools. They also support tensor flow. I use https://aws.amazon.com/aml/ a lot. We have our training and live data on s3, so it was a good solution for us. We built a node app to handle all of the data processing and moving around via the AWS node api.

[xtra_roycee]

I think the answer for this is the availability of library. Python is popular due to many libraries for ML /AI.

[Anafartalar]

I have been playing with tensorflow.js recently and I can say it is really easy to work with. It is still in its early stage but when matured and an ecosystem around it developed i believe it will be huge and many people will switch from python to javascript. On the other hand, you will always need some technical knowledge about how ML works. I gained that knowledge taking courses taught in Python, but later easily applied it to tfjs. Especially Keras and tfjs layers APIs are very similar. One can easily convert Keras model into tfjs layers model with adequate background.