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