

PyBrain -- the Python Machine Learning Library - jnaut
http://github.com/pybrain/pybrain/

======
leecho0
This is mainly a neural network library, it has svm support mainly for
comparison.

It still can't replace weka... which you can kinda use with python
<http://weka.wikispaces.com/Can+I+use+WEKA+from+Python%3F>

~~~
jnaut
This post's scope was about an ML library in Python. There was in fact no such
argument made about replacement of any other much more evolved project like
Weka, Mallet, etc.

But still, thanks for bringing forth the fact that there are much more
sophisticated libraries/pkgs that exist, though in Java, but can be used with
Python. Which is actually true for any Java code, i.e. it is accessible in
Python, I use JPype for it, among the few other available options for the
purpose.

~~~
falsestprophet
Weka and mallet sound like excellent excuses to learn Scala or Groovy.

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hack_edu
This isn't the first time I've seen 'learning,' 'cognitive,' or 'brain' Python
libraries come up in on HN. I'm always interested, but can never glean enough
from them to understand what to use them for.

Can anyone offer anecdotal experience your machine learning project?

~~~
jnaut
I can see in your profile "about:librarian". Hence I am a bit confused as to
why you don't know where to use ML, but still, I will go ahead and just
scratch the surface for you. Since listing all the fields where ML is/can-be
used will require a book by itself. :-)

Well I shall limit my answer to two simple examples from the web and in the
vicinity of your profile, so that you find it more interesting.

Did you know that ML is one of the key components of Google(1) search, yes,
the one that you might be using day in and day out.

Did you know that all the sites offering you personalized recommendations like
"people who bought this book also liked this book", use ML.

Why don't you do a fun experiment. Take up a programming language (I suggest
Python) and write an algo (using PyBrain and NN's in it) that reads and learns
from habits of the students (book borrowers in this case) and then recommends
them on what they should read next, based on what the machine has learned from
their past behavior. It won't be perfect and best prediction, rather it will
be pathetic at the begining, but it will recommend good and relevant books as
time goes by and the machine/algo knows more about the students.

(1)for that matter any good search engine.

Have fun!!

~~~
jnaut
Well!! Did I just give a good product idea?? """A recommendation engine for
use in libraries to learn from reading habits of students(borrowers)and hence
suggest next reads.""" Not sure how much money can it make though. :-)

Edit: Online book/movie selling/renting engines do that, but not sure of real
world libraries doing that. Especially now , when the books are going "e". :-)

~~~
hack_edu
Yeah, there's already plenty of libraries and library-vendors that offer
recommendations (Librarything, OCLC's Navigator). Even some open-source online
library catalogs have rudimentary recommendations based on subject categories.
Libraries likely don't offer recommendations based on a user's checkout
history because of a long tradition of utmost privacy concerning a patron's
information.

As a librarian though, I'm much more interested in tracking and understanding
uses of scholarly journal articles. Most research in academic libraries occurs
online, and the current vendors do little but index and provide a search
engine.

~~~
jnaut
Good point: """Libraries likely don't offer recommendations based on a user's
checkout history because of a long tradition of utmost privacy concerning a
patron's information."""

That's where privacy statements like these come in:

<http://www.goodreads.com/about/privacy> [courtesy j2d2]

