Julia Programming For Data Science & Machine Learning

[ciboga]

ciboga submitted a new resource:

Julia Programming For Data Science & Machine Learning - Learn the Power of Julia High performance for Data Science and Machine Learning with nearly C

Description

Do you like Python, you enjoy writing python code. It's very easy to code in python. But python is slow. So production require very high performance computing.
So we need a language which is easy to work like python and as fast as low level programming language like C.
Julia is the programming language which looks like Python and execute like C.
If you want to learn next generation fast...

Read more about this resource...

 

[dikk]

Small rant, sorry, but I had to:

"like" the bullshit the course author says that python is slow. Of course it is. There is no cython, and no pypy. Also numpy does not make it faster than plain arrays. Of course numba (which is a jit compiler using llvm - so similar to julia) does not make it faster. Of course there is no asyncio package in python (there is). Of course asyncio cannot be boosted even further with things like uvloop (native code), etc. I really love these bullshitting authors.

Julia is a good language. It copied a lot from python (also a bit from ruby and javascript). It is jit compiled (so, slower startup than python, if we need to compare). It has this so called multiple dispatch built-into the language which is basically calling different functions with the same name, based on the type of arguments. So what. Can be done in python as well (by checking types for instance).

The fact is julia is getting some tailwind as people in data science began to take notice and started using it. That's it. If you know python, it is almost the same, so if you learn it, one more language can go onto the cv. The situation is like once you know french, learning italian or spanish is not that huge of an accomplishment.