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~~NOTOC~~ ====== Python and Machine Learning resources ====== ===== ML open source software and data ===== * The [[http://archive.ics.uci.edu/ml/index.html | UCI]] machine learning data repository. * [[http://mloss.org/software/|MLOSS]]: machine learning open source software repository. * [[http://rodrigob.github.io/are_we_there_yet/build/classification_datasets_results.html | Are we there yet?]] recent progress on challenging computer vision datasets. * [[http://www.kaggle.com/competitions | ML competitions]]. ===== Python ===== === Resources for learning python === * [[https://docs.python.org/3/tutorial/ | The official Python tutorial]] * [[http://greenteapress.com/wp/think-python-2e/|Think Python]], on-line book by Allen Downey * [[http://learnpythonthehardway.org/book/|Learn Python the hard way]] (not updated to Python 3) === Python resources === * [[http://pythonconquerstheuniverse.wordpress.com/category/python-debugger/|Python Debugging Techniques]] * [[http://docs.python.org/library/index.html|The Python Standard Library]] * [[http://ipython.org/|IPython]]: a better Python interpreter. ===== Python on ... ===== ==== ... MS Windows ==== * [[http://docs.python.org/using/windows.html|Using Python on Windows]] ==== ... Macs ==== * [[http://docs.python.org/using/mac.html|Using Python on Macs]] ===== Python in ... ===== ==== .. in Emacs ====== * [[http://www.gnu.org/software/emacs/tour/|A Guided Tour of Emacs]], helps answer the question "Why emacs?" ==== .. in Eclipse ===== * [[http://pydev.org/|Pydev for Eclipse]] (if you must...) ====== numpy, matplotlib, scipy ====== * [[http://www.google.com/url?sa=t&source=web&cd=10&ved=0CGkQFjAJ&url=http%3A%2F%2Fm.friendfeed-media.com%2Fde093ffcc58b8447f5ac2e8ddd83074d8cf9c4bd&rct=j&q=numpy%20list%20of%20array%20values%20without%20copying&ei=duPCTc_NHobiiALIzfyjAw&usg=AFQjCNHkcn0RBhgCCAUP7xqO2pSA34nlQA|The NumPy Array: A Structure for Efficient Numerical Computation]], by Stéfan van der Walt, S. Chris Colbert, and Gaël Varoquaux * [[http://neuroscience.telenczuk.pl/wp-content/uploads/2010/07/python_tools_for_science.pdf|Python Tools for Science]], by Bartosz Telenczuk * [[http://www.scipy.org/Tentative_NumPy_Tutorial|Tentative (basic) tutorial]] * [[http://www.scipy.org/Numpy_Example_List|Example list]] * [[http://docs.scipy.org/doc/numpy/reference/|Reference guide]] * [[http://showmedo.com/videotutorials/video?fromSeriesID=1037&name=10370000|Introducing Numpy Arrays]], video. Many other related vides can be [[http://showmedo.com/videotutorials/numpy|found here]]. * For installing on MS Windows, see [[http://www.scipy.org/Installing_SciPy/Windows|Installing SciPy / Windows]]. ====== Matplotlib ====== * Save and edit the customization file [[http://matplotlib.sourceforge.net/users/customizing.html#customizing-matplotlib|described here]] to modify how matplotlib makes plots. * Here is a [[http://www.oneminutepython.com/|nice short tutorial]] on how to combine matplotlib plots within a gui application based on wxWidgets and wxPython. ====== LaTeX ====== Lots of tutorials and quick starts out there: * [[http://tobi.oetiker.ch/lshort/lshort.pdf|The Not So Short Introduction to LATEX 2ε or LATEX 2ε in 157 minutes]] by Tobias Oetiker, Hubert Partl, Irene Hyna and Elisabeth Schlegl, with an excellent index useful for looking up commands * [[http://soundandcomplete.com/2010/05/13/emacs-as-the-ultimate-latex-editor/|Emacs as the Ultimate LaTeX Editor]], by Piotr Kaźmierczak * [[http://www.maths.adelaide.edu.au/anthony.roberts/LaTeX/ltxqstart.html|LaTeX: from quick and dirty to style and finesse]], by Tony Roberts * [[http://tug.org/tutorials/tugindia/|Online tutorials on LaTeX]] by the Indian TeX Users Group * [[http://www.andy-roberts.net/writing/latex|Getting to Grips with LaTeX]] by Andrew Roberts ===== Tools for LaTex ===== There are specific editors and GUI programs to help you with LaTex (e.g. texmaker, lyx, and kile for linux, which are installed on CS machines, and miktex for windows). Personally, I either do things at the commandline and use emacs/aquamacs for editing or use one of two very good online systems: ([[https://www.overleaf.com/ | Overleaf]] or [[https://www.sharelatex.com/ | ShareLatex]]). ===== Latex on Windows and Macs ===== * [[http://www.latex-project.org/ftp.html|Obtaining LaTeX]], includes links to [[http://www.tug.org/protext/|ProTeXT]] for Windows, and [[http://www.tug.org/mactex/|MacTeX]] for Macs. ===== Remote Access to CS Department Machines ===== See the [[https://www.cs.colostate.edu/wiki/Remote_Access|Remote Access]] page department wiki. ====== Matrices ====== * [[http://www.johndcook.com/blog/2010/01/19/dont-invert-that-matrix/|Don't Invert that Matrix]], by John Cook * [[http://orion.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf|The Matrix Cookbook]], by Kaare Brandt Petersen and Michael Syskind Pedersen ===== Machine Learning Societies, Journals and Conferences ===== * [[http://machinelearning.org/|The International Machine Learning Society]] and its [[http://machinelearning.org/icml.html|International Conference on Machine Learning]] * [[http://jmlr.csail.mit.edu/|Journal of Machine Learning Research]], free, on-line * [[http://www.mitpressjournals.org/loi/neco|Neural Computation]] * [[http://nips.cc/|Neural Information Processing Systems]] conference.