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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.

0 votes

How to develop small workable embeddings for debugging

GloVe has a wide selection of pre-trained vectorizers. You can simply choose one of the smaller datasets, e.g. the Wikipedia trained model from https://github.com/stanfordnlp/GloVe/blob/master/README. …
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5 votes

Why is predicted rainfall by LSTM coming negative for some data points?

Currently your model is not restricted from guessing any number. In this case, you may want to use something like a ReLU activation function to restrict your output domain. The ReLU activation needs …
kbrose's user avatar
  • 1,932
7 votes
Accepted

Convnet training error does not decrease

In your convnet code, you compute the cross entropy manually: cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y_conv), reduction_indices=[1])) train_step = tf.train.AdamOptimizer(1e-5).mi …
kbrose's user avatar
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1 vote

Why does my Keras Conv Net only return 1?

It is only outputting 1 because softmax makes no sense when given a single input. Softmax computed with only one input $x$ is equivalent to $\frac{e^x}{e^x} = 1$. In other words, the line model.add( …
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2 votes
Accepted

What are the benefits of having ML in js?

There are a lot of services that offer free or very cheap hosting of static websites. If you are able to implement your ML model in JS this allows you to deploy your product/app/whatever easily and wi …
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1 vote

Solving multi label image classification using TimeDistributed dense layer

There is no need to repeat any features. What you want to do is change your activation function from softmax to sigmoid, otherwise leaving everything else as it would normally be done for binary class …
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1 vote

Checkers playing Neural Network evolved with Genetic Algorithm becomes too sensitive to inpu...

Full disclosure, I'm not at all an expert on genetic algorithms, so take this with a grain of salt. First of all, I'm not sure the $r$ parameter in $w'=w*m'*r$ makes sense. You say it's a random stan …
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