> All of these languages have libraries that produce the same results, the difficulty is mangling the data into the correct input format. Python's list comprehensions are much, much easier to use than MATLAB matrices, R's data frames, Java's ArrayLists, etc.

At the end of the day, for machine learning applications, your data is in a tabular format. (in Python, a pandas data frame) Yes, Python has a few tricks like list comprehensions for speeding up data processing into that analyzable form. R has a few tricks for processing tabular data as well. (e.g. dplyr).

There are tradeoffs and the skill is finding which works best. Using a single programming language is a bad philosophy even for non-statistical developers.