Network structure inspired by simplified models of biological neurons (brain cells).
I'm trying to train a classifier via PyTorch. However, I am experiencing problems with training when I feed the model …
python neural-network deep-learning classification pytorchI am lost in the scikit learn 0.18 user manual (http://scikit-learn.org/dev/modules/generated/sklearn.neural_network.MLPClassifier.html#…
python python-2.7 scikit-learn neural-networkCould someone please explain to me how to update the bias throughout backpropagation? I've read quite a few books, but …
math machine-learning artificial-intelligence neural-networkI recently came across tf.nn.sparse_softmax_cross_entropy_with_logits and I can not figure out what the …
neural-network tensorflow softmax cross-entropyI was going through this example of a LSTM language model on github (link). What it does in general is …
neural-network deep-learning lstm pytorch contiguousAfter training a word2vec model using python gensim, how do you find the number of words in the model's …
python neural-network nlp gensim word2vecI am using a modified predict.py for testing a pruned SqueezeNet Model [phung@archlinux SqueezeNet-Pruning]$ python predict.py --image 3_100.…
numpy neural-network pytorch pruningwhile I'm reading in how to build ANN in pybrain, they say: Train the network for some epochs. Usually you …
machine-learning artificial-intelligence neural-network pybrainI'm trying to pass the output of one layer into two different layers and then join them back together. However, …
python neural-network keras recurrent-neural-networkI'm trying to implement a neural network that classifies images into one of the two discrete categories. The problem is, …
python-3.x numpy neural-network deep-learning gradient-descent