ML5.js is recommended for educators, beginners, artists, and developers who want to quickly implement machine learning models in web applications. It is also suitable for creative coding projects and interactive applications where simplicity and ease of use are important.
Based on our record, Supabase seems to be a lot more popular than ML5.js. While we know about 521 links to Supabase, we've tracked only 10 mentions of ML5.js. 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.
This tutorial explains how I improved my application's read performance using Postgres materialized views in Supabase. - Source: dev.to / 4 days ago
All examples in this blog are tested on Supabase, an open source backend-as-a-service (BaaS) platform that simplifies backend development for web and mobile applications. Supabase provides full support for Postgres databases. - Source: dev.to / 10 days ago
But relying on these safeguards isn't as simple as sprinkling BEGIN and COMMIT into your code. You still have to address challenges like race conditions, constraint violations, and mid-transaction failures across API layers. Supabase helps solve these issues by building on Postgres and handling the transaction logic directly at the database itself. It exposes the logic through streamlined interfaces that preserve... - Source: dev.to / 11 days ago
If you don't have an account, head over to supabase.com and sign up. Once you're in, create a new project. Give it a name, generate a secure database password, and choose a region. Your project will be ready in a couple of minutes. - Source: dev.to / 11 days ago
Instead of setting up a local Postgres instance, I decided to use Supabase because it provides a fully managed, hosted Postgres database out of the box, simplifying the setup time and database management. This allows us to focus entirely on writing and deploying the application code without worrying about infrastructure details. First, visit Supabase and create a free account if you don't have one yet. - Source: dev.to / 16 days ago
Ml5.js: Built on top of TensorFlow.js, it provides a user-friendly interface for implementing machine learning in web applications.โ. - Source: dev.to / 5 months ago
Important APIs - ml5 for in-browser detection, face-api that uses tensorflow-node to accelerate on-server detection. VueUse for a bunch of useful component tools like the QR Code generator. Yahoo's Gifshot for creating gif files in-browser etc. - Source: dev.to / almost 3 years ago
See also: https://ml5js.org/ "The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.". - Source: Hacker News / about 3 years ago
I used ml5js.org , p5js.org and https://teachablemachine.withgoogle.com to train the Banana images. When you create a new image project on Teachable Machine, you can output the p5js and basically use it right out of the box - I customized js, css, and html from there. Source: over 3 years ago
Going forward: I'll be 100% into JavaScript. You can use JavaScript in so many fields nowadays. Websites React, Mobile Apps React Native, Machine Learning TensorFlow & ML5, Desktop Applications Electron, and of course the backend Node as well. It's kind of a no-brainer. Of course, they all have specific languages that are better, but for now, JavaScript is a bit of a catch-all. - Source: dev.to / over 3 years ago
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
Machine Learning Playground - Breathtaking visuals for learning ML techniques.
Next.js - A small framework for server-rendered universal JavaScript apps
Amazon Machine Learning - Machine learning made easy for developers of any skill level
AppWrite - Appwrite provides web and mobile developers with a set of easy-to-use and integrate REST APIs to manage their core backend needs.
Lobe - Visual tool for building custom deep learning models