I’ve found a solution, if anyone wants to know:

In tensorflow scale the data normally:

from sklearn.preprocessing import StandardScaler

scaler = StandardScaler()

scaler.fit(X_train)

X_train = scaler.transform(X_train)

X_test = scaler.transform(X_test)

To get the mean type: scaler.mean_

To get the std type: scaler.scale_

Copy and paste these figures into your Arduino code using the formula below:

The standard score of a sample `x`

is calculated as:

z = (x - u) / s

where `u`

is the mean of the training samples or zero if `with_mean=False`

, and `s`

is the standard deviation of the training samples or one if `with_std=False`

.

Example code below:

float Sensor1 = (sensorReading1 - mean_) / scale_;