Questions tagged [neural]
The neural tag has no usage guidance.
14
questions
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1answer
13 views
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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0answers
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 ...
0
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1answer
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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1answer
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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0answers
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 ...
1
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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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0answers
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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0answers
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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0answers
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 ...
1
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0answers
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 ...
0
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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,...
1
vote
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 ...
0
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1answer
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 ...
