kwertzzz

9 ms·

61.
by kwertzzz 7y ago
This is interesting to know, because Julia uses exactly the same approach[1] (now I know where it comes from). To me it seems to be the ideal solution: use the in-place normalize!(X) where performance is important, otherwise use the more co
62.
by kwertzzz 7y ago
I am not a R user (using primarily julia and python), but can you expand on the insecure aspect of CRAN. Do you refer to (potentially) missing package signing (similar to [1])? I am not aware that python or julia support this either. Or is
63.
by kwertzzz 7y ago
Actually, for plotting I prefer to use PyPlot in Julia which is based on matplotlib which is very mature and complete in my opinion. I tried to use other (more native) plotting packages like GR, Plots and Makie but they did not provide all
64.
by kwertzzz 7y ago
The interoperability of Julia and Python is really good (Julia calling Python and vice-versa). There is also the possibility to call R functions (but I do not use it personally). To some degree, one can leverage python's ecosystem in J
65.
by kwertzzz 8y ago
Julia fits the bill quite well in my opinion: * features: you have an extensive standard library, macros, high level constructs (like generators, asynchronous programming, ...) * performance: julia is based on LLVM and as long the code is t
66.
by kwertzzz 8y ago
OK, I see. In any case, even if the performance would not match Tensforflow on TPU this is a major achievement. After all, Google made the TPUs specifically for Tensorflow. I would not have imagined that it was so "easy" to replac
67.
by kwertzzz 8y ago
This is a very impressive work. I am wondering why it was compared against PyTorch (just on the CPU) and not against Tensorflow (on CPU and TPU) or do I miss something?
68.
by kwertzzz 8y ago
This is really a great achievement. I am wondering how much communication was necessary between the cores during the computation or is the problem a so called "embarrassingly parallel" workload where the work could be split into i
69.
by kwertzzz 8y ago
This is indeed a very good idea. In Julia, the package author defines the range of supported Julia version. Most package actually just say "version 0.6 or later". The JuliaDB package was just been updated preventing the installati
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by kwertzzz 8y ago
Sorry for the delay, but here is an example code: https://gist.github.com/Alexander-Barth/c8eb764f400cdb7a1eb5... Do not hesitate to tell me if I missed something to optimize the python code. If somebody has numba, pyt
71.
by kwertzzz 8y ago
Thank you for the info about numpy.matmul. However this feels quite clumsy to use a function call for a matrix operator, especially when you have several chained. I think that this is an good move to get rid of matrix class (I just didn&#x2
72.
by kwertzzz 8y ago
I am giving a class on numerical methods and one student choose to use python (while my example code was in Julia). It was a pain to see how this student was constantly shooting himself in the foot due some particular behaviors of python an