Edge Impulse Inc. / room-classifier-demo
This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.
Creating your first impulse (100% complete)
Acquire data
Every Machine Learning project starts with data. You can capture data from a development board or your phone, or import data you already collected.
Design an impulse
Teach the model to interpret previously unseen data, based on historical data. Use this to categorize new data, or to find anomalies in sensor readings.
Deploy
Package the complete impulse up, from signal processing code to trained model, and deploy it on your device. This ensures that the impulse runs with low latency and without requiring a network connection.
Download block output
| Title | Type | Size | |
|---|---|---|---|
| Flatten training data | NPY file | 836 windows | |
| Flatten training labels | NPY file | 836 windows | |
| Flatten testing data | NPY file | 228 windows | |
| Flatten testing labels | NPY file | 228 windows | |
| NN Classifier model | TensorFlow Lite (float32) | 7 KB | |
| NN Classifier model | TensorFlow Lite (int8 quantized) | 3 KB | |
| NN Classifier model | TensorFlow SavedModel | 17 KB | |
| NN Classifier model | Keras h5 model | 6 KB |
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Summary
Data collected
9m 20sProject info
| Project ID | 79896 |
| Project version | 2 |
| License | No license attached |
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