Use MinMaxScaler , label encoder, one hot encoder , keras prediction file for later prediction
You could use pickle to store your encoders/scalers/etc. It is a common way of storing Python objects

from sklearn.preprocessing import LabelEncoder
import pickle

# Fit a label encoder
le = LabelEncoder()
X = le.fit_transform(X)

# Pickle the encoder for later use
with open('path/and/name', 'wb') as f:
    pickle.dump(le, f)


Then when you have it stored it can be used again by loading the pickle

# Read the pickle from file
with open('path/and/name', 'rb') as f:
    le = pickle.load(f)

# Use the already fitted encoder to transform new data
X = le.transform(X)


Then repeat the process for your all your preprocessing objects