..
|
logs
|
10-1.lenet_in_keras.ipynb
|
10-2.alexnet_in_keras.ipynb
|
10-3.vggnet_in_keras.ipynb
|
10-4.transfer_learning_in_keras.ipynb
|
11-1.natural_language_preprocessing.ipynb
|
11-10.multi_convnet_sentiment_classifier.ipynb
|
11-2.dense_sentiment_classifier.ipynb
|
11-3.convolutional_sentiment_classifier.ipynb
|
11-4.rnn_sentiment_classifier.ipynb
|
11-5.lstm_sentiment_classifier.ipynb
|
11-6.bi_lstm_sentiment_classifier.ipynb
|
11-7.stacked_bi_lstm_sentiment_classifier.ipynb
|
11-8.gru_sentiment_classifier.ipynb
|
11-9.conv_lstm_stack_sentiment_classifier.ipynb
|
12-1.generative_adversarial_network.ipynb
|
13-1.cartpole_dqn.ipynb
|
14-1.fashion_mnist_pixel_by_pixel.ipynb
|
14-2.pytorch.ipynb
|
5-1.shallow_net_in_keras.ipynb
|
5-2.mnist_digit_pixel_by_pixel.ipynb
|
6-1.sigmoid_function.ipynb
|
7-1.softmax_demo.ipynb
|
8-1.quadratic_cost.ipynb
|
8-2.cross_entropy_cost.ipynb
|
8-3.measuring_speed_of_learning.ipynb
|
8-4.intermediate_net_in_keras.ipynb
|
9-1.weight_initialization.ipynb
|
9-2.deep_net_in_keras.ipynb
|
9-3.regression_in_keras.ipynb
|
9-4.deep_net_in_keras_with_tensorboard.ipynb
|
clean_gutenberg_model.w2v
|
clean_gutenberg_tsne.csv
|
hot-dog-not-hot-dog.tar.gz
|