Teach a machine using your camera, live in the browser. No coding required.
is highly experimental.
If you’re new to machine learning, visit the site on a desktop for a helpful first-time tutorial and better performance.Sorry, looks like your browser or device doesn't support this experiment. Learn more about Teachable Machine here. Or try visiting this site on a desktop computer in a browser like Chrome.
Share your video below, or redo it.
This experiment lets anyone explore how machine learning works, in a fun, hands-on way. You can teach a machine to using your camera, live in the browser – no coding required. You train a neural network locally on your device, without sending any images to a server. That’s how it responds so quickly to you. Watch this video to learn more:
Here are some links to things people have done so far: Make your hand say moo. Rock out by wiggling your fingers. And stay tuned, we’ll add more examples here soon. (Want to share something with us? Use the record button and share it on social media with #teachablemachine so we can check it out.)
Capture at least 30 images per class. Be aware of when you’re pressing and releasing the button (that’s when it starts/stops capturing images). And you might need to capture lots of angles or variations of whatever it is you want your machine to recognize.
Don’t worry. Keep playing around. Seeing what works and what doesn’t is one way to explore how machine learning works. Keep in mind that your machine doesn’t have an understanding of higher level concepts, like faces or objects. It’s learning through the examples you give it. So if it’s not working the way you want, you might want to click the x to reset your classes and try out different approaches.
Check out Wekinator by Rebecca Fiebrink, one of the inspirations for this project. It lets anyone use machine learning through simple actions instead of code. Here are some interactive guides for learning about machine learning. And check out other fun projects like this and this.
No. All the training is happening locally on your device.
The image classification is powered by a neural network. It was made possible by Nikhil Thorat and Daniel Smilkov, the team behind deeplearn.js. It’s an open-source library that allows web developers to train and run machine learning models locally in the browser. The code for this experiment is open-sourced here on Github.
We also made a boilerplate project which demonstrates how to use deeplearn.js to create projects of your own like Teachable Machine here.