--- title: Scalers keywords: fastai sidebar: home_sidebar summary: "Utils for scaling data" description: "Utils for scaling data" nb_path: "nbs/data__scalers.ipynb" ---
data = 100 + 0.5*np.random.randn(1000)
print('Mean:', data.mean())
print('STD:', data.std())
scaler = Scaler(normalizer='std')
data_norm = scaler.scale(x=data, mask=np.ones(data.shape))
print('Mean:', data_norm.mean())
print('STD:', data_norm.std())