(Replying to PARENT post)
Does Julia have good substitutes for Numpy / Scipy / sk-learn / Pandas / Matplotlib / Keras / Tensorflow / Theano yet either natively (for Numpy) or from libraries (for others)? Ease of analysis being almost at the level of matlab is why I stick with python. I would love to be able to switch to something that doesn't have such a heavy handed approach at the top.
๐คdaveguy๐8y๐ผ0๐จ๏ธ0
(Replying to PARENT post)
Not surprising.
Just take any function you write and write code_native( your_function, () )
Knowing that the JIT is actually executing means a lot to me. For investment banks this means lower cost (quants can write code that goes into production) and lower latencies.
๐คeb0la๐8y๐ผ0๐จ๏ธ0
(Replying to PARENT post)
Any idea what it was written in before?
๐คtnecniv๐8y๐ผ0๐จ๏ธ0
(Replying to PARENT post)
https://juliacomputing.com/case-studies/blackrock.html