Reenvío, creo que puede ser de interés para varios.
---------- Forwarded message ----------
From: Martin Rocamora - IIE
Date: Tue, May 20, 2014 at 2:09 PM
Subject: Seminario - python para computacion cientifica
To: todos_iie@fing.edu.uy
Cc: paola@fing.edu.uy, lj@eumus.edu.uy, apardo@ucu.edu.uy
La semana proxima tendremos la visita de Thomas Grill, investigador de
la OFAI (Austria), que trabaja en el grupo de Intelligent Music
Processing and Machine Learning.
Estara dando un seminario de python para computacion cientifica, cuyos
detalles estan mas abajo. Estan todos invitados y les agradezco que
avisen a otros posibles interesados.
Fecha: Martes 27 de Mayo Hora : 14:00 a 17:00 hrs Lugar: Salon azul,
tercer piso de Facultad de Ingenieria (UDELAR)
This workshop is an introduction into scientific computing with
python. Attendees should already have a basic understanding of Python
(having worked through the official tutorial). Topics covered include
working with multidimensional data, plotting and storing data, tools
from the domain of machine learning and an excursion into methods of
speeding up computation.
Come with your laptop which should have installed
Python 2.7.x (http://python.org) ... if you have 2.6 already
installed, this works as well.
numerical python aka numpy, http://www.numpy.org/, version 1.8.x
matplotlib http://matplotlib.org/, version 1.3.x
scientific python aka scipy, http://www.scipy.org/, version 0.13.x
scikit-learn aka sklearn, http://scikit-learn.org/, version 0.14
Optional, but quite helpful is ipython, http://ipython.org/, version 2.0
Advanced packages for speed optimization (optional):
cython - http://cython.org/
theano - http://deeplearning.net/software/theano/
pyfftw3 - https://launchpad.net/pyfftw/
Official tutorial: https://docs.python.org/2/tutorial
Thomas Grill
http://grrrr.org