Teachable Machine by Google

Teachable Machine is a fast, easy way to create machine learning models for your sites, apps, and more.

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This is the main page. There is a brief introduction. Press Get Started button to start.

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I will make an example project to analyse photos this time. Choose Image Project button.

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Name the classifications and add the pictures that correspond to that classification. The more data, the better. This is an example, so I’ll add 10 pictures each. The goal of this model is to find out who the Red Velvet members are by looking at their photos.

{/* <!– 다음은 학습 과정을 설정합니다. Advanced를 눌러 세부 사항을 설정할 수 있습니다. 각 설정값에 대한 자세한 설명은 (?) 아이콘 위에 커서를 올리면 볼 수 있습니다. 간단하게 설명하자면

• Epochs는 학습을 몇 번 반복할 지를 나타냅니다.
• Batch Size는 한 번 학습할 때 데이터의 크기를 나타냅니다.
• Learning Rate는 얼마나 빠르게 학습을 할 지를 나타냅니다. 일반적으로 0.001을 사용합니다. 설정을 다 했다면 Train Model 버튼을 누릅니다.–> */}

The following sets up the learning process: You can set the details by pressing Advanced button. For a detailed description of each setting, hover your cursor over the (?) icon.

• Epochs indicates how many times to repeat the learning process.
• Batch Sizeis the size of the data on a single epoch.
• Learning Rate represents how fast the machine will learn. Typically, use 0.001.

Press Train Model button to train with these settings.

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Test with another picture you didn’t use when learning to see if it works properly. In these two cases, Wendy and Irene are well matched.

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If the model learned well, you can save the final model and use it for other projects.

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However, there were cases where one of Joy’s photos was misjudged as Irene. In this case, each category is not sufficiently divided because only 10 photos are included in the input data. For more accurate classification that is available for real use, you will need to have plenty of learning data.