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) 6 KB
NN Classifier model TensorFlow Lite (int8 quantized) 4 KB
NN Classifier model TensorFlow Lite (int8 quantized with float32 input and output) 4 KB
NN Classifier model TensorFlow SavedModel 16 KB
Anomaly detection model JSON 974 Bytes

Summary

Data collected
2m 9s

Project info

Project ID 33126
Project version 6