Teachable Machine is an easy-to-use web-based tool for creating machine learning models with no expertise or coding required. It can be used to recognize images, sounds, and poses, by gathering and grouping examples into classes that you want the computer to learn.

Training a model is fast, and you can instantly test it out to see if it can correctly classify new examples. Models can be exported for use in sites, apps, and more, and you can choose to use it entirely on-device without any webcam or microphone data leaving your computer.

Teachable Machine is compatible with TensorFlow, ML5.js, p5.js, Coral, Framer, node.js, Glitch, and Arduino, and you can use files or capture examples live.

Tutorials are available to help users get started, and there are plenty of projects that have been made with Teachable Machine, such as a DIY experiment connecting Arduino and Teachable Machine, an assistive communication device, a game controller using a webcam and a piece of paper, and a physical machine that you can teach to rapidly recognize and sort objects.

It can even be used to create a video game controller. It is a powerful tool for creating machine learning models with a wide range of applications.

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Model generation Teachable Machine 4.0(1)

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Teachable Machine was manually vetted by our editorial team and was first featured on January 29th 2023.

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Most impacted jobs

Machine Learning Engineer

Impact: 90%

Tasks: 1330

AIs: 10,826

Director Of Engineering

Impact: 90%

Tasks: 1180

AIs: 10,884

Pros and Cons

Pros

Web-based tool

No coding required

Can recognize images, sounds, poses

Fast model training

Instant testing available

Export models for use

On-device usage option

Compatible with TensorFlow

Compatible with ML5.js

Compatible with p5.js

Compatible with Coral

Compatible with Framer

Compatible with node.js

Compatible with Glitch

Compatible with Arduino

Can use files or live input

Available tutorials

Can create game controller

Wide range of applications

Can classify audio

Can classify body positions

Several project examples

Models work with JavaScript

Export to different formats

Available lessons & activities

Train models with own data

Supports file and live capturing

Several supported output formats

Cons

No coding required limits customization

Requires substantial data input

Limited to three modalities: image, sound, pose

Compatibility issues with other platforms

Dependent on user provided class grouping

Models may lack complexity

Errors in classification not easily rectified

No advanced analytics

Limited export formats

No user community for troubleshooting

Q&A

What is Teachable Machine?

Teachable Machine is a web-based tool that makes creating machine learning models simple, quick, and accessible to all. No coding or specific expertise is required. With the use of Teachable Machine, one can train a computer to recognize specific images, sounds, and poses.

How can I use Teachable Machine?

To use Teachable Machine, follow these three steps: 1) Gather and group examples into classes, or categories, that you want the computer to learn. 2) Train your model and instantly test it out to see if it can accurately classify new examples. 3) Export your model for your projects, which could include websites, applications, and more.

Can Teachable Machine recognize images, sounds, and poses?

Yes, Teachable Machine can recognize images, sounds, and poses. It accomplishes this by gathering and grouping examples into classes that the computer is taught to identify.

How quickly can Teachable Machine train a model?

Teachable Machine is designed to train a model quickly. However, the exact time may vary based on the complexity of the task and the amount of data used for training.

Can I test my models instantly with Teachable Machine?

Yes, one of the features of Teachable Machine is the ability to test models instantly. After a model is trained, it can be immediately tested to see if it can correctly classify new examples.

What can I do with the models created by Teachable Machine?

Models created by Teachable Machine can be exported for use in different applications, such as websites, mobile apps, games, and more. It can be used for a range of applications like creating a game controller, communicating through facial gestures, or teaching a physical machine to sort objects, among others.

Can Teachable Machine operate entirely on-device?

Yes, Teachable Machine can operate entirely on-device. This means that no webcam or microphone data has to leave your computer, ensuring privacy.

What languages and technologies is Teachable Machine compatible with?

Teachable Machine is compatible with several languages and technologies including TensorFlow, ML5.js, p5.js, Coral, Framer, node.js, Glitch, and Arduino.

What sort of tutorials are available for Teachable Machine?

A number of tutorials are available for Teachable Machine, including guides on creating a model that can identify if a banana is ripe, detects simple sounds made by the user, and recognizes the way a user's head is tilted.

Can I use files or live examples with Teachable Machine?

Yes, Teachable Machine offers flexibility in the input it can learn from. One can use files or can capture examples in real time.

Can I use Teachable Machine to create a game controller?

Yes, Teachable Machine can be used to create a game controller. For instance, a project named 'Teachable Arcade' used Teachable Machine to train a video game controller.

Can Teachable Machine sort objects?

Yes, Teachable Machine can be used to teach a physical machine to sort objects. A project called 'Teachable Sorter' showcases a machine that can rapidly recognize and sort objects using custom machine learning models.

Are there any successful projects made with Teachable Machine?

There have been several successful projects made with Teachable Machine. This includes the 'Tiny Sorter', 'Project Euphonia', 'Teachable Snake', and the 'Teachable Sorter'.

How respectful is Teachable Machine of my data?

Teachable Machine is designed with respect for user data. The data gathered for training models is only used to improve the performance of the created model and is not stored or used elsewhere. It can also be operated entirely on-device, ensuring no webcam or microphone data leaves your computer.

How can Teachable Machine be utilized in assistive technology?

Teachable Machine can be utilized in assistive technology. An example is 'Project Euphonia', where Steve Saling uses Teachable Machine to communicate in new ways, such as using facial gestures to trigger sounds.

Can I teach a physical machine using Teachable Machine?

Yes, a physical machine can be trained using Teachable Machine. An example is the 'Teachable Sorter', a physical machine trained to rapidly recognize and sort objects.

Can I use Teachable Machine to recognize specific body positions?

Yes, Teachable Machine can be used to recognize specific body positions. Users can provide files or strike poses live in their webcam to train the model.

Can Teachable Machine recognize simple sounds I make?

Yes, Teachable Machine can recognize simple sounds. There's a tutorial available that guides users on creating a model that can detect simple sounds they make.

Where can I find more examples of what's been done with Teachable Machine?

More examples of applications created by Teachable Machine can be found on the 'Experiments with Google' website.

Is Teachable Machine suitable for learning about machine learning?

Yes, Teachable Machine is suitable for learning about machine learning. It has been used in various educational settings, with lessons and activities developed for students to understand the bias in algorithmic systems, interactive systems, and machine learning concepts.