Louis Moreau / Arduino KWS
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 | |
|---|---|---|---|
| MFE training data | NPY file | 345 windows | |
| MFE training labels | NPY file | 345 windows | |
| MFE testing data | NPY file | 70 windows | |
| MFE testing labels | NPY file | 70 windows | |
| Transfer learning (Keyword Spotting) model | TensorFlow Lite (float32) | 216 KB | |
| Transfer learning (Keyword Spotting) model | TensorFlow Lite (int8 quantized) | 101 KB | |
| Transfer learning (Keyword Spotting) model | TensorFlow SavedModel | 243 KB | |
| Transfer learning (Keyword Spotting) model | Keras h5 model | 206 KB |
Clone project
Summary
Data collected
7m 2sProject info
| Project ID | 142511 |
| Project version | 1 |
| License | Apache 2.0 |
|
|
