Keras Deep Learning Cookbook

Full code listing

Following is the full code listing of the recipe Classification for spam detection:

from keras.layers import Embedding, Dense, LSTMfrom keras.models import Sequentialfrom keras.preprocessing.text import Tokenizerfrom keras.preprocessing.sequence import pad_sequencesimport numpy as npfrom sklearn.metrics import confusion_matriximport pandas as pd# get datasetdata = pd.read_csv('/spam-detection/spam_dataset.csv')texts = []classes = []for i, label in enumerate(data['Class']):    texts.append(data['Text'][i])    if label == 'ham':        classes.append(0)    else:        classes.append(1)texts = np.asarray(texts)classes = np.asarray(classes)print("number of texts :", len(texts))print("number of labels: ", len(classes))# number of words used as features ...