Deep Learning is an area of machine learning whose goal is to learn complex functions using special neural network architectures that are "deep" (consist of many layers).
How to count the total number of parameters in a PyTorch model? Something similar to model.count_params() in Keras.
deep-learning pytorchIn this page, it is said that: [...] skip-gram inverts contexts and targets, and tries to predict each context word from …
nlp tensorflow deep-learning word2vec word-embeddingI am new in Tensorflow and I am trying to build model which will be able to perform OCR on …
python tensorflow deep-learning mnistWhat will be the output size, if the input to convolution layer of neural network is an image of size 128…
python machine-learning deep-learning conv-neural-networkLooking at an example 'solver.prototxt', posted on BVLC/caffe git, there is a training meta parameter weight_decay: 0.04 What …
machine-learning neural-network deep-learning caffe gradient-descentI just try to find out how I can use Caffe. To do so, I just took a look at …
machine-learning neural-network deep-learning caffe gradient-descentI'm studying TensorFlow and how to use it, even if I'm not an expert of neural networks and deep learning (…
tensorflow deep-learningI am looking for a possibility to append data to an existing dataset inside a .h5 file using Python (h5…
python numpy deep-learning hdf5 h5pyI started to play with TensorFlow two days ago and I'm wondering if there is the triplet and the contrastive …
tensorflow deep-learningSometimes I run into a problem: OOM when allocating tensor with shape e.q. OOM when allocating tensor with shape (1024, 100, 160) …
machine-learning neural-network deep-learning keras gradient-descent