Node.js
VS Code
ExpressJS
Laravel
Django
Ruby on Rails
ASP.NET
React
Scale Nucleus
ML Image Classifier
Aquarium
Prodigy
mlblocks
PerceptiLabs
Machine Learning Playground
Roboflow Universe
Node.jsBased on our record, Node.js seems to be a lot more popular than Scale Nucleus. While we know about 921 links to Node.js, we've tracked only 2 mentions of Scale Nucleus. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Node >= 22 or higher installed on their local development machine. - Source: dev.to / about 2 months ago
TypeScript / Node.js: Excellent for building asynchronous backend systems that must stream text data smoothly to thousands of users simultaneously. - Source: dev.to / about 2 months ago
Because Node.js operates on a single-threaded asynchronous runtime, it is inherently vulnerable to processes that hog the CPU for too long. I absolutely cringe whenever I see developers blindly copy-pasting complex regular expressions from StackOverflow without actually testing their performance impact. - Source: dev.to / about 2 months ago
This tutorial walks you through setting up a simple Docker Compose project that serves two Node web servers over HTTPS using Caddy as a reverse proxy. You will learn how to use mkcert to generate wildcard certificates and the minimal configuration needed in the Caddyfile and docker-compose.yml to get it all working. - Source: dev.to / 3 months ago
Node.js: This is required for Hardhat. You can check if your terminal has it installed by running node -v. It will show a version number, if it is already available. If not, download the LTS version from https://nodejs.org/en, install it, then reopen your terminal and recheck to confirm successful installation. - Source: dev.to / 4 months ago
At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 4 years ago
To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 5 years ago
VS Code - Build and debug modern web and cloud applications, by Microsoft
ML Image Classifier - Quickly train custom machine learning models in your browser
ExpressJS - Sinatra inspired web development framework for node.js -- insanely fast, flexible, and simple
Aquarium - Improve ML models by improving datasets theyโre trained on
Laravel - A PHP Framework For Web Artisans
Prodigy - Radically efficient machine teaching