Questions tagged [neural]

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Relationship between Sigmoid and Gaussing Distribution

I was reading this article where I came across the following statement in the context of "Why do we use sigmoid activation function in Neural Nets?": The assumption of a dependent variable to follow ...
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44 views

Data Augmentation Multi Outputs

This question is asked several times here on SE, but I havent been able to find the right answer. I'm trying to build a network with 1 input and 2 outputs. I don't have a lot of data so I would like ...
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23 views

why do we operate with graphical models in VAE, if there are no probabilites involved?

In the variational autoencoder, I often see graphical models e.g. $P(X|Z)$ for the decoder, but when I looked at code, I don't see any random variables, I see just deterministic network, with ...
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2k views

Keras error “Failed to find data adapter that can handle input” while trying to train a model

I've been following a tutorial on training a model and I've stumbled across an error that I've been struggling to find a solution for. The code for the model training is bellow: ...
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8 views

weight updation in neural networks

I have a question after a batch of data has been passed gradients are calculated through backpropagating the error from the last layer to the first layer then weights are updated from the first layer ...
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1answer
20 views

Application of Machine learning in modelling experimental system as a PhD topic

I am working as a control Engineer in a high energy physics lab. I am looking for a PhD thesis topic. Our experimental system is highly non linear and can't be modeled using standard white box ...
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15 views

LSTM model visualisation

I'm studying this LSTM model https://www.kaggle.com/paoloripamonti/twitter-sentiment-analysis I wonder how the model would look like in a visualization so you see a lot on internet. Is this a good ...
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29 views

Does an LSTM model with one hidden layer has much advantages over a RNN or NN?

Does an LSTM model with one hidden layer has much advantages over a RNN or NN? Cause the network is not deep/large
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61 views

Price Prediction via Neural Network (Keras)

I am trying to do call price prediction my data set looks something like this ...
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121 views

Serious doubts on Categorical embedding

I am still having many doubts about the working of categorical embedding. In particular I have 2 points not clear: 1. Are 1-Hot variables converted to a lower dim vector? 2. What target are neural ...
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1k views

Binary Classification of Numeric Sequences with Keras and LSTMs

I'm attempting to use a sequence of numbers (of fixed length) in order to predict a binary output (either 1 or 0) using Keras and a recurrent neural network. Each training example/sequence has 10 ...
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1answer
330 views

ValueError: Error when checking input: expected conv2d_13_input to have shape (3, 150, 150) but got array with shape (150, 150, 3)

I am trying to train the model, I keep ending up with this ValueError: ValueError: Error when checking input: expected conv2d_13_input to have shape (3, 150, 150) but got array with shape (150, 150,...
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1answer
34 views

Transfer learning - small database

I am trying to use transfer learning in medical (ultrasound pictures). The problem is - I have very limited picture database = 400 (360+40). I am using resnet50 (I don't think this is important but ...
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31 views

Adapting Neural Network to new domain without labels

Is there an approach for the following problem: Lets say, I trained a neural network on a big dataset for categorizing different fruits in $k$ classes. Afterwards I got a nice model, which performs ...