Iván

Buenos Aires, Argenina

Jul
17
awarded Popular Question
Apr
25
accepted find all usages of certain methods and functions in a python package
Apr
25
comment find all usages of certain methods and functions in a python package
Thank you very much for your answer! In general it seems that the code that you provided works great. However with some codes I am experiencing an error that I can not debug... Do you have any hint or idea of what it is causing it?
Apr
24
comment find all usages of certain methods and functions in a python package
@MartijnPieters I just edited my question a little bit, I think I was not precise enough. I want to find the lines where the functions/methods are called.
Apr
24
revised find all usages of certain methods and functions in a python package
more precise question
Apr
24
asked find all usages of certain methods and functions in a python package
Mar
20
awarded Student
Jan
8
awarded Scholar
Jan
8
accepted Unwanted space before commas in ModernCV
Jan
8
awarded Student
Jan
7
asked Unwanted space before commas in ModernCV
2018
Dec
13
comment Number of parameters keras dense layer with a 2D input
But in that case how the dot product is performed? I mean, how to you perform the dot product when you have a 2D matrix? when is a 1D array is easy because is $$\vec{x}\dot\vec{w}$$ but when $x$ is 2D which dimension do you choose?
Dec
13
asked Number of parameters keras dense layer with a 2D input
Dec
10
revised Shape of 1D convolution output on a 2D data using keras
added 487 characters in body
Dec
10
comment Shape of 1D convolution output on a 2D data using keras
I understand the reduction from 128 to 119, but what I don't understand is why the feature dimension changes. For example, if I use Conv1D(filters = 1, kernel_size= 10, activation='relu'), then the output dimension is going to be (None, 119, 1), giving rise to only one feature after the convolution. What is going on in this dimension, which operation is performed to go from from 9 --> 1?
Dec
10
answered Training multiple keras models and combining outputs to determine losses
Dec
10
asked Shape of 1D convolution output on a 2D data using keras
Oct
31
comment how many points do I need to uniquely determine a nonlinear monotonically increasing function?
@EthanBolker Where I can find more info about your answer?
Oct
31
comment how many points do I need to uniquely determine a nonlinear monotonically increasing function?
@Federico $f(x;a_1, a_2)$ should verify that $f(0)=0$ since I also asked for that, and in that case I think that one point is enough to point will give the value of $a_1=a_2$ and then f(x)=0. However a constant function is not an increasing function I think.
Oct
31
asked how many points do I need to uniquely determine a nonlinear monotonically increasing function?
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