175 karma · joined December 10, 2014
Math as a language is just a DSL which carries a lot of historical burden that is not friendly at all. Programming languages can achieve same level of abstraction with more clarity. Math instead added too much specific syntactic sugar(bad is multiply(b, a, d), log a is log(10, a) or log(e, a)), operator overload (/ for divide and dy/dx for differentiation operator, same grammar for scalar and matrix multiplication, one of which is communicative while the other is not), and complicated design (integral would be much clearer if we write integrate(target=ax, over=x, from=0, to=10) instead of the original one).
I never mention 5000 years of History, only 1500. I am trying to not related with any politics here.
By your reasoning if there exists some propaganda then my personal experience should not be trusted?
In addiction, the long history is not created by CCP but following the Chinese scholar tradition. It is correct that CCP used it for creating nationalism, but they did not fabricate the whole thing.
To know more about Chinese culture not from [politic fueled](https://en.wikipedia.org/wiki/John_Ross_(academic)) books, I suggest you to read The [Problem of China](http://www.freeclassicebooks.com/Bertrand%20Russell/The%20Pr...) by Bertrand Russell. It is authored by a well-known scholar and written before the CCP exists in case you accuse me of suggesting you propaganda. The opinions by the book may be too old but at least the facts are unbiased IMO.
As a normal Chinese with standard Chinese education till 10th grade (then move to a foreign country), I can understand fragments of writings carved in stones 1500 years ago in museums, which I felt quite amazing.
YOLO is a quite standard feed-forward model in my opinion. I mean the math part, which I am more concerned with.
I have never used Theano before, my idea from it is that Tensorflow followed its static graph approach.
If data and model are mixed, it often resort to line-by-line debugging to zone out the real problem, which often takes more time.
For trying out deep learning, or build on existing models, pytorch or keras may be easier to grasp. But when making new models that involves a lot of math, the Theano/Tensorflow is more helpful IMO.
It is also the same for technology/AI. They may not improve our quality of life, but they allow more powerful armies that would defeat those who resist them.
It's sad but it's true.
It was my favorite because of its excellent documentation and community support.
Maybe something like constructive category theory would give us a better way to formally put ideas in ...