Viam includes a built-in machine learning (ML) service which provides your machine with the ability to learn from data and adjust its behavior based on insights gathered from that data. Common use cases include:
- Object detection and classification which enable machines to detect people, animals, plants, or other objects with bounding boxes, and to perform actions when they are detected.
- Speech recognition, natural language processing, and speech synthesis, which enable machines to verbally communicate with us.
However, your machine can make use of machine learning with nearly any kind of data.
Use machine learning with your machine
|2. Create a Dataset and Label
Once you have collected data, label your data and create a dataset in preparation for training machine learning models.
|3. Train or upload an ML model
|4. Deploy your ML model
To make use of ML models with your machine, use the built-in ML model service to deploy and run the model.
|5. Configure a service
For other usage, you can use a modular resource to integrate it with your machine.
|6. Test your detector or classifier
Test your mlmodel detector or classifier.
Add an ML model modular-resource-based service which uses TensorFlow Lite to classify audio samples.
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