A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle.
Tensorflow offers a nice LSTM wrapper. rnn_cell.BasicLSTM(num_units, forget_bias=1.0, input_size=None, state_is_tuple=False, …
neural-network tensorflow lstm recurrent-neural-networkI am trying RNN on a variable length multivariate sequence classification problem. I have defined following function to get the …
python tensorflow recurrent-neural-network gated-recurrent-unitTrying to implement a minimal toy RNN example in tensorflow. The goal is to learn a mapping from the input …
tensorflow recurrent-neural-networkI trained a tf.nn.seq2seq.model_with_buckets with seq2seq = tf.nn.seq2seq.embedding_attention_seq2…
tensorflow recurrent-neural-networkI am trying to learn how to build RNN for Speech Recognition using TensorFlow. As a start, I wanted to …
tensorflow word2vec recurrent-neural-network language-modelwith tf.variable_scope('forward'): cell_img_fwd = tf.nn.rnn_cell.GRUCell(hidden_state_size, hidden_state_size) img_…
tensorflow recurrent-neural-network gated-recurrent-unitI am new to deep learning and currently working on using LSTMs for language modeling. I was looking at the …
deep-learning lstm recurrent-neural-network pytorchI'm using Keras to build a LSTM and tuning it by doing gradient descent with an external cost function. So …
python performance keras recurrent-neural-network reinforcement-learningI have been given some data of this format and the following details: person1, day1, feature1, feature2, ..., featureN, label person1, …
python tensorflow lstm recurrent-neural-network tflearnSince an LSTM RNN uses previous events to predict current sequences, why do we shuffle the training data? Don't we …
machine-learning keras lstm recurrent-neural-network