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Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

sebastianraschka.com

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Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#41

Post by sampo »

noobermin wrote: post #35
jordigh wrote: post #20

Earlier quoted context omitted.

For someone who has never programmed before, Matlab may be more intuitive. Yes, this is Matlab's target audience: programmers who will not call themselves "programmers". In recent versions, they have tried even harder to hide the code away from the user, by trying to make everything work by clicking on buttons. I have heard from many Matlab users call themselves "not a programmer". They don't feel like writing softwa…

On balance, I've met people who claim they are intermediate programmers and use matlab only, and are freaked to shit when they see higher order functions in other languages, or even the idea of passing a "function", like, say, a pointer to a function, into another function, even though function pointers have existed since C.

> function pointers have existed since C

Also at least in ALGOL 68, COBOL, and FORTRAN 77. Maybe earlier, too.

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#42

Post by leni536 »

And there is nothing wrong with C++. For linear algebra I use the armadillo library and it's really a nice wrapper around LAPACK and BLAS (and fast!). For some reason scientists are somewhat afraid of C++. For some reason you "have to" prototype in an "easier" language. Sure, you can't use C++ as a calculator as opposed to interpreted languages, but I see people being stuck with their computations at the prototyping language and eventually not bringing it to a faster platform.

Point being: C++ is not hard for scientific calculations.

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#43

Post by rasbt »

a_bonobo wrote: post #39

>I think it [Perl] is still quite common in the bioinformatics field though!? That's true - many day-to-day tasks in bioinformatics are more or less plain-text parsing [1], and Perl excels in parsing text and quickly using regular expressions. "My" generation of bioinformaticians doing data cleanup and analysis (20-30) uses Python, sometimes because plotting is nicer, the language is easier to get into, it's more com…

Thanks for the insights! Also here, this comment would make an interesting addition to a "Feedback" section at the end of the article to give people a broader view on this topic. May I have your permission to post your comment below the article?

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#44

Post by rasbt »

leni536 wrote: post #42

And there is nothing wrong with C++. For linear algebra I use the armadillo library and it's really a nice wrapper around LAPACK and BLAS (and fast!). For some reason scientists are somewhat afraid of C++. For some reason you "have to" prototype in an "easier" language. Sure, you can't use C++ as a calculator as opposed to interpreted languages, but I see people being stuck with their computations at the prototyping…

I agree with you. However, note that many people who are using Python for writing scientific code make use of C/C++ in one way or the other (aside from NumPy, SciPy, and Theano). For example, many people write the "most intensive" computations down in C/C++/Cython if they call those functions frequently -- Python becomes a wrapper. One example that pops into my mind is khmer (https://github.com/dib-lab/khmer)

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#45

Post by a_bonobo »

rasbt wrote: post #43
a_bonobo wrote: post #39

>I think it [Perl] is still quite common in the bioinformatics field though!? That's true - many day-to-day tasks in bioinformatics are more or less plain-text parsing [1], and Perl excels in parsing text and quickly using regular expressions. "My" generation of bioinformaticians doing data cleanup and analysis (20-30) uses Python, sometimes because plotting is nicer, the language is easier to get into, it's more com…

Thanks for the insights! Also here, this comment would make an interesting addition to a "Feedback" section at the end of the article to give people a broader view on this topic. May I have your permission to post your comment below the article?

Of course you have my permission :)

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#46

Post by rasbt »

Adam_O wrote: post #17

From the perspective of a student, most of the good online analytics/data analysis/stats courses use R, so it is hard to get away from it while learning the material. Once you get the base concepts down, switching to python shouldn't be hard. I think most people still prefer ggplot2 for visualization though. Whenever I use R I feel like a statistician, I can feel that 'cold rigor' emanating from the language. But in…

Yes, I think you are right. Out of curiosity, when I browsed over Coursera's course catalog, most data science related material seems to be taught in Matlab or R (however, there are also others, e.g., Klein's Linear Algebra class in Python). Personally, I think that instructors shouldn't enforce a language requirement. I believe for big platforms such as coursera it shouldn't be to hard to run an respective interpreter to check the code/answer uploaded by a student.

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#47

Post by RA_Fisher »

rasbt wrote: post #44
leni536 wrote: post #42

And there is nothing wrong with C++. For linear algebra I use the armadillo library and it's really a nice wrapper around LAPACK and BLAS (and fast!). For some reason scientists are somewhat afraid of C++. For some reason you "have to" prototype in an "easier" language. Sure, you can't use C++ as a calculator as opposed to interpreted languages, but I see people being stuck with their computations at the prototyping…

I agree with you. However, note that many people who are using Python for writing scientific code make use of C/C++ in one way or the other (aside from NumPy, SciPy, and Theano). For example, many people write the "most intensive" computations down in C/C++/Cython if they call those functions frequently -- Python becomes a wrapper. One example that pops into my mind is khmer ( https://github.com/dib-lab/khmer )

I believe S (ancestor of R) started as C glue at Bell Labs. I've heard it said a few times that R is slow, but that doesn't really make much sense if your bottleneck routines are R calls to C++.

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#48

Post by rm999 »

rasbt wrote: post #11
rm999 wrote: post #7

I switched from mostly using R to Python about a year ago for gluing together my data pipeline (from data source all the way to production models and frontends/visualizations). It hasn't really impacted what I'm capable of doing or my productivity, except the standard extra googling that comes in the first couple years I use any language. The main reason I went for Python is purely practical: it's a language people o…

I went through the very same process :). I really like your comment, you highlight something that I forgot to mention in this clarity "It makes it easier for me to collaborate in many different ways: share tools with other teams, transfer ownership of my code, get help when I need". Would you mind if I add it as to a "other people's experiences" section at the bottom of the article?

Definitely feel free to add that!

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#49

Post by cinquemb »

leni536 wrote: post #42

And there is nothing wrong with C++. For linear algebra I use the armadillo library and it's really a nice wrapper around LAPACK and BLAS (and fast!). For some reason scientists are somewhat afraid of C++. For some reason you "have to" prototype in an "easier" language. Sure, you can't use C++ as a calculator as opposed to interpreted languages, but I see people being stuck with their computations at the prototyping…

I see this a lot in my lab (days/weeks to run computations and analysis that could take minutes/hours), and I used to offer to help the postdocs/phd students port their code from matlab to C/C++, but I've mostly given up on offering unless they ask for help, or if it seems like fun. I also think it's because they mostly think they won't work on these things again (which is kind of weird to think about since they spent most of their life working to get to this point, but that's another conversation).

Aside, I think armadillo is pretty great, especially going back and forth with other matrix libraries, also nice wrapper around OpenBLAS which made not running something on a cluster more bearable.

Re: Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

#50

Post by pekk »

idunning wrote: post #5

As someone who almost exclusively uses Julia for their day-to-day work (and side projects), I think most of the author's thoughts about Julia are correct. I think the language is great, and using it makes my life better. There are some packages that are actually better than any of their equivalents in other languages, in my opinion. On the other hand, I've also got a higher tolerance for things not being perfect, I c…

Could you name some of the packages you think are better than any of their equivalents?
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