80 lines
2.9 KiB
Markdown
80 lines
2.9 KiB
Markdown
# mlpractical
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## Machine Learning Practical (INFR11119)
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**Note:** At this point, you can go straight to 00_Introduction notebook - which contains more information.
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To run the notebooks (and later the code you are going to write within this course)
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you are expected to have installed the following packages:
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<ul>
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<li>python 2.7+</li>
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<li>numpy (anything above 1.6, 1.9+ recommended, optimally compiled with some BLAS library [MKL, OpenBLAS, ATLAS, etc.)</li>
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<li>scipy (optional, but may be useful to do some tests)</li>
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<li>matplotlib (for plotting)</li>
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<li>ipython (v3.0+, 4.0 recommended)</li>
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<li>notebook (notebooks are in version 4.0)</li>
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</ul>
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You can install them straight away on your personal computer,
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there is also a notebook tutorial (00_Introduction) on how to
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do this (particularly) on DICE, and what configuration you
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are expected to have installed. For now, it suffices if you
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get the software working on your personal computers so you can
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start ipython notebook server and open the inital introductory
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tutorial (which will be made publicitly available next Monday).
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### Installing the software on personal computers
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#### On Windows:
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Download and install the Anaconda package
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(https://store.continuum.io/cshop/anaconda/)
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#### On Mac (use macports):
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<ul>
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<li>Install macports following instructions at https://www.macports.org/install.php</li>
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<li>Install the relevant python packages in macports
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<ul>
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<li> sudo port install py27-scipy +openblas </li>
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<li> sudo port install py27-ipython +notebook </li>
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<li> sudo port install py27-notebook </li>
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<li> sudo port install py27-matplotlib </li>
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<li> sudo port select --set python python27 </li>
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<li> sudo port select --set ipython2 py27-ipython </li>
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<li> sudo port select --set ipython py27-ipython </li>
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</ul>
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</ul>
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Also, make sure that your $PATH has /opt/local/bin before /usr/bin
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so you pick up the version of python you just installed
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#### On DICE (we will do this during the first lab)
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### Getting the mlpractical repository
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Assuming ~/mlpractical is a target workspace you want to use during
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this course (where ~ denotes your home path, i.e. /home/user1).
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To start, open the terminal and clone the github mlpractical
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repository to your local disk:
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git clone https://github.com/CSTR-Edinburgh/mlpractical.git
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(Note: you can do it from your git account if you have one as the
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above just clone the repo as anonymous user, though it does not
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matter at this point, as you are not required to submit pull requests, but you are **welcomed** to do so if you think some aspects of the notebooks can be improved!)
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Naviagate to the checked out directory (cd ~/mlpractical) and type:
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ipython notebook
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This should start ipython notebook server and open the browser with the page
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listing files/subdirs in the current directory.
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To update the repository (for example, on Monday),
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enter ~/mlpractical and type git pull.
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