Nordic Semiconductor / nrf_accel_sim
A simple project using simulated acceleration readouts. Used by machine_learning application in nRF Connect SDK.
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 | |
|---|---|---|---|
| Spectral features training data | NPY file | 4312 windows | |
| Spectral features training labels | NPY file | 4312 windows | |
| Spectral features testing data | NPY file | 1652 windows | |
| Spectral features testing labels | NPY file | 1652 windows | |
| NN Classifier model | TensorFlow Lite (float32) | 5 KB | |
| NN Classifier model | TensorFlow Lite (int8 quantized) | 3 KB | |
| NN Classifier model | TensorFlow SavedModel | 11 KB | |
| NN Classifier model | Keras h5 model | 5 KB | |
| Anomaly detection model | JSON | 977 Bytes |
Clone project
Run this model
Summary
Data collected
2m 9sProject info
| Project ID | 18121 |
| Project version | 12 |
| License | Apache 2.0 |
