utils/normalize.py

import pandas as pd

def normalize(data: pd.DataFrame) -> pd.DataFrame:
    data_mean = data.mean(axis=0)
    data_std = data.std(axis=0)
    return ((data - data_mean) / data_std).fillna(0.)
feat(Model): trying to get to a model that can train 2021-11-11 17:53:24 +01:00			`import pandas as pd`
feat(Model): continued with the keras model scaffolding 2021-11-10 14:51:12 +01:00
feat(Model): trying to get to a model that can train 2021-11-11 17:53:24 +01:00			`def normalize(data: pd.DataFrame) -> pd.DataFrame:`
			`data_mean = data.mean(axis=0)`
			`data_std = data.std(axis=0)`
feat(Model): now successfully training the basic LSTM model 2021-11-11 18:29:05 +01:00			`return ((data - data_mean) / data_std).fillna(0.)`