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Results tagged with deep-learning
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user 41591
a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hidden layers), but also with some sort of Probabilistic Graphical Models.
1
vote
1
answer
150
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Can Sequence to sequence models be used to convert code from one programming language to ano...
Is it possible to convert a code from one language to another using sequence to sequence programming. if not sequence to sequence, which algorithm can i use to do this?
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0
votes
1
answer
848
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training when Multiple labels per image
I have multiple labels per image. is it better to train taking each each label separately or should i mark all the labels present as 1 in the same image? which method is better? i will be using CNN ar …
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28
votes
2
answers
37k
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What is the advantage of using log softmax instead of softmax?
Are there any advantages to using log softmax over softmax? What are the reasons to choose one over the other?
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0
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3
answers
647
views
can machine learning/Deep learning used to minimize an objective function?
I have data of construction site and am wondering if i can use machine learning to reduce the cost it takes to build a building. But, as far as i know, Machine learning can only does function approxim …
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3
votes
1
answer
538
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training model on random samples from a large dataset
I have a huge data set(More than 1 million data points).My dataset is text. i am doing NER on it to identify few entities. if i randomly choose 100 data points from the total data set and train my mod …
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0
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1
answer
4k
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Does Convolution kernel size affect number of channels?
I am going through Dilated Residual Network blog post. In this, Under 2.Multi-scale Context aggregation heading, author mentioned this.
The last one is the 1×1 convolutions for mapping the number …
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1
vote
1
answer
119
views
how to encode labels for relationship extraction
I am trying to extract relationship from text. So, lets take the following text
"He went to movie. but, they went to school"
So, here the relationship's are "He and Movie", "they and school".
How c …
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1
vote
1
answer
2k
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padding on mnist for LeNet Architecture
LeNet accepts 32X32 image. So, to use LeNet for MNIST dataset,we have to change the size from 28X28 to 32X32. I came across This implementation. i am confused about how the following line of code work …
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2
votes
Time Series Classification using LSTM
First thing i suggest you to try is to change the learning rate.
Change the following code
model.compile(loss='binary_crossentropy', optimiser='adam',metrics='accuracy'])
to
from keras import op …
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0
votes
400 positive and 13000 negative: how to split dataset up (train, test, validation)
Simple thing to do is to use Stratified sampling as suggested by @n1k31t4. Other thing which people usually do with images is to Image Augmentation. So, you can try to rotate,tilt, mirror your positiv …
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4
votes
3
answers
196
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Are dimensionality reduction techniques useful in deep learning
I have been working on machine learning and noticed that most of the time, dimensionality reduction techniques like PCA and t-SNE are used in machine learning, but I rarely noticed anyone doing it for …
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15
votes
4
answers
4k
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Is Gradient Descent central to every optimizer?
I want to know whether Gradient descent is the main algorithm used in optimizers like Adam, Adagrad, RMSProp and several other optimizers.
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