Want to bring Teachable Machine into your own web creations?
We’re working on a library called teachablemachine.js which will let you do just that. Here’s the first remixable demo you can play with to get a sneak peek at what’s possible:
Hello Wizard - This demo shows how you can drop a machine learning “training wizard” on top of your website with just a few lines of code.
Look out for more demos coming soon.
Email us at [email protected] if you’d like to chat more about teachablemachine.js. We’re interested in hearing what developers might like to create with it.
Teachable Machine is a web-based tool that makes creating machine learning models fast, easy, and accessible for everyone. You can try it here.
Educators, artists, students, innovators, makers of all kinds – really, anyone who has an idea they want to explore. No prerequisite machine learning knowledge required.
You train a computer to recognize your images, sounds, and poses without writing any machine learning code. Then, use your model in your own projects, sites, apps, and more.
This repository contains two components of Teachable Machine:
-
A libraries section that contains all of the machine learning code used in Teachable Machine. Under the hood we use Tensorflow.js, a library for machine learning in Javascript, to train and run the models you make in your web browser. The
librariessection also contains the API for image, audio, and pose helper libraries that make it easier to use the models exported by Teachable Machine in your own projects. -
A snippets section that contains markdown snippets that are being displayed inside the export panel in Teachable Machine. These snippets contain code and instructions on how to use the exported models from Teachable Machine in languages like Javascript, Java and Python.
You have a few options:
- Email us at [email protected].
- Share your projects using #teachablemachine on Twitter or on the Experiments with Google page.
- Open an issue in this repository.
This is an experiment, not an official Google product. We’ll do our best to support and maintain this experiment but your mileage may vary.
We encourage open sourcing projects as a way of learning from each other. Please respect our and other creators’ rights, including copyright and trademark rights when present, when sharing these works and creating derivative work. If you want more info on Google's policy, you can find that here.