turf VS Brain.js

to measure distances and convert between our parameters I'm using TurfJS, for which binding is even more trivial:

Turf.js is an open-source geospatial analysis library that can process various location data, such as the center of gravity and distance calculations.

Isochrones are manually calculated using turf.js assuming 1.2m/s walking speed after the subway trip. These are simple buffers around each station/prior isochrone and do not take the street network into account.

Not to take away from you learning, which I think is awesome, I was wondering if you know about http://turfjs.org/ which provides a lot of simple modules … and is surprisingly hard to find. Their `distance` modules may be relevant in this case.

you can use client side libraries like Turfjs to do buffers https://github.com/Turfjs/turf/tree/master/packages/turf-buffer

Tools: custom Javascript (with heavy use of turf.js) for data processing and creating the 3D model, Blender, 3D printing, lost wax casting

I've integrated https://turfjs.org/ with mapbox before and it was pretty fun

References Amazon Location Service Turf.js MapLibre GL JS Leaflet OpenLayers Cesium Mapbox GL JS

Brain.js

One, Two, Three, and so on. ANYone does use JS for machine learning. Though that's unconventional, python is by far the leading language for ML. Maybe you meant to say "EVERYone"?

for more details please check brain.js official documentation.

Brain.js: This is a library for training and deploying neural networks in JavaScript. It provides a simple and flexible API for building feedforward and recurrent networks.

Next comes machine learning: thought you'd use python for that? Tensorflow? Wrong. You use brain.js for that. 😎

Brain.js

Brain.js - Machine-learning framework.