Neural Network Projects with Python

Putting it all together

We have covered a lot in this chapter. Let's consolidate all our code here:

from keras.datasets import imdbfrom keras.preprocessing import sequencefrom keras.models import Sequentialfrom keras.layers import Embeddingfrom keras.layers import Dense, Embeddingfrom keras.layers import LSTMfrom matplotlib import pyplot as pltfrom sklearn.metrics import confusion_matriximport seaborn as sns# Import IMDB datasettraining_set, testing_set = imdb.load_data(num_words = 10000)X_train, y_train = training_setX_test, y_test = testing_setprint("Number of training samples = {}".format(X_train.shape[0]))print("Number of testing samples = {}".format(X_test.shape[0]))# Zero-PaddingX_train_padded = sequence.pad_sequences(X_train, maxlen= ...