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).
I am trying to implement a LSTM based speech recognizer. So far I could set up bidirectional LSTM (i think …
deep-learning keras lstmI am following this tutorial for learning TensorFlow Slim but upon running the following code for Inception: import numpy as …
python machine-learning tensorflow computer-vision deep-learningI would like to understand what tf.global_variables_initializer does in a bit more detail. A sparse description is …
tensorflow deep-learningI have a dataset containing grayscale images and I want to train a state-of-the-art CNN on them. I'd very much …
python tensorflow machine-learning keras deep-learningI am trying to train the following CNN as follows, but I keep getting the same error regarding .cuda() and …
python python-3.x machine-learning deep-learning pytorchThe Keras documentation could be improved here. After reading through this, I still do not understand what this does exactly: …
python deep-learning kerasI was trying to replicate How to use packing for variable-length sequence inputs for rnn but I guess I first …
deep-learning pytorch recurrent-neural-network tensor zero-paddingI have downloaded the MNIST dataset from LeCun site. What I want is to write the Python code in order …
python tensorflow machine-learning deep-learning mnistI'm trying to have an in-depth understanding of how PyTorch Tensor memory model works. # input numpy array In [91]: arr = np.…
python numpy multidimensional-array deep-learning pytorchOpenAI's REINFORCE and actor-critic example for reinforcement learning has the following code: REINFORCE: policy_loss = torch.cat(policy_loss).sum() …
python machine-learning deep-learning pytorch