Network structure inspired by simplified models of biological neurons (brain cells).
In the following TensorFlow function, we must feed the activation of artificial neurons in the final layer. That I understand. …
tensorflow machine-learning neural-network deep-learning cross-entropyI want to make a simple neural network which uses the ReLU function. Can someone give me a clue of …
python numpy machine-learning neural-networkIt is a principal question, regarding the theory of neural networks: Why do we have to normalize the input for …
machine-learning neural-network normalizationUsing Anaconda Python 2.7 Windows 10. I am training a language model using the Keras exmaple: print('Build model...') model = Sequential() …
python neural-network nlp deep-learning kerasI am trying to understand the role of the Flatten function in Keras. Below is my code, which is a …
machine-learning tensorflow neural-network deep-learning kerasI am trying to assign a new value to a tensorflow variable in python. import tensorflow as tf import numpy …
python tensorflow neural-network deep-learning variable-assignmentI have a simple NN model for detecting hand-written digits from a 28x28px image written in python using Keras (…
python machine-learning neural-network keras theanoI have a data matrix in "one-hot encoding" (all ones and zeros) with 260,000 rows and 35 columns. I am using Keras …
python keras neural-network theano loss-functionI was looking at the docs of tensorflow about tf.nn.conv2d here. But I can't understand what it …
neural-network tensorflowI am looking for some relatively simple data sets for testing and comparing different training methods for artificial neural networks. …
neural-network training-data