
Ask HN: Why are most ML and AI projects written in Python? - roh26it
Does it have an inherent advantage?<p>Most people just happened to write the libraries in it for other people to build on?<p>Something else?
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urlwolf
Python has good bindings to venerable libraries in C and fortran that nobody
would want to implement from scratch. Python libs like numpy and scipy were
very convenient ways to call the highly optimized code in say BLAS. Then
scikit-learn came and made machine learning easy for the masses. Before, libs
in R would provide different methods but they were anything but unified
(things like CARET notwithstanding).

In the last 2-3 years the main driver was deep learning. Since the whole point
was to run on a GPU and CUDA remains a pain of low-level C, python made it
very palatable.

R has lost the race by not jumping on the deep learning train. Scala shows
promise because of Spark, its killer app.

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roh26it
I also hear Python is very Math like so ML practitioners tend to like it a
little more?

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davelnewton
Reasonable language, well-known libraries.

There are other approaches in other languages that are gaining ground, but
little offer the "easy in" that numpy/scipy/pandas provides.

~~~
roh26it
"other languages"

Which ones are doing well apart from Python? Any cutting edge stuff?

~~~
davelnewton
Scala and Clojure both have existing environments.

~~~
urlwolf
Scala far more than Clojure at this point.

