[ad_1] import tensorflow as tf from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense, Dropout, LSTM from sklearn.preprocessing import MinMaxScaler import numpy as np # Load and preprocess data # … # Build the neural network model = Sequential() model.add(LSTM(50, return_sequences=True, input_shape=(X_train.shape[1], 1))) model.add(LSTM(50, return_sequences=False)) model.add(Dense(25)) model.add(Dense(1)) # Compile the model model.compile(optimizer=”adam”, loss=”mean_squared_error”) # Train the
