Visualize Neural Network Architecture Preliminaries /* Load libraries */ from keras import models from keras import layers from IPython.display import SVG from keras.utils.vis_utils import model_to_dot from keras.utils import plot_model Using TensorFlow backend. Construct Neural Network Architecture /* Start neural network */ network = models.Sequential() /* Add fully connected layer with a ReLU activation function */ …
Visualize Loss History Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers import matplotlib.pyplot as plt /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Data /* Set the number of features we want */ number_of_features …
Tuning Neural Network Hyperparameters Preliminaries /* Load libraries */ import numpy as np from keras import models from keras import layers from keras.wrappers.scikit_learn import KerasClassifier from sklearn.model_selection import GridSearchCV from sklearn.datasets import make_classification /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Generate Target And Feature Data /* Number of features */ number_of_features = 100 …
Save Model Training Progress Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers from keras.callbacks import ModelCheckpoint #/* Set random seed */ np.random.seed(0) Load IMDB Movie Review Data /* Set the number of features we want */ number_of_features = …
Preprocessing Data For Neural Networks Typically, a neural network’s parameters are initialized (i.e. created) as small random numbers. Neural networks often behave poorly when the feature values much larger than parameter values. Furthermore, since an observation’s feature values will are combined as they pass through individual units, it is important that all features have the …
Neural Network Weight Regularization Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers from keras import regularizers /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Text Data /* Set the number of features we want …
Neural Network Early Stopping Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers from keras.callbacks import EarlyStopping, ModelCheckpoint /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Text Data /* Set the number of features we …
LSTM Recurrent Neural Network Oftentimes we have text data that we want to classify. While it is possible to use a type of convolutional network, we are going to focus on a more popular option: the recurrent neural network. The key feature of recurrent neural networks is that information loops back in the network. This …
Feedforward Neural Network For Multiclass Classification Preliminaries /* Load libraries */ import numpy as np from keras.datasets import reuters from keras.utils.np_utils import to_categorical from keras.preprocessing.text import Tokenizer from keras import models from keras import layers /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Data /* Set the number of features we …
Feedforward Neural Network For Binary Classification Preliminaries /* Load libraries */ import numpy as np from keras.datasets import imdb from keras.preprocessing.text import Tokenizer from keras import models from keras import layers /* Set random seed */ np.random.seed(0) Using TensorFlow backend. Load Movie Review Data /* Set the number of features we want */ number_of_features = …