Setting Maching Learning on OSX

Setting up machine learning tools (numpy, scipy, matplotlib, scikit-learn, ...) can be a pain (why can they just use a decent OS? :).

We are lucky to have Ben Kim now with us at Adconion, and he posted the following:

Mac OS X Lion Software Installs

1. Install compilers
   1. Install XCode 4.x from the App Store
      1. Install Command Line Tools in Preferences/Download
   2. Install gcc, g++, and gfortran compilers
      1. Download tar file
      2. Extract to /
         1. tar -xvf abc.tar -C /
   3. Reference http://sites.google.com/site/dwhipp/tutorials/mac_compilers
2. Install Homebrew
   1. Run the install command using ruby

      1. ruby <(curl -fsSkL raw.github.com/mxcl/homebrew/go)

   2. brew doctor
      1. chown /usr/local folders listed
      2. Place /usr/local/bin before /usr/bin in path
   3. Reference https://github.com/mxcl/homebrew/wiki/installation
3. Install python using brew
   1. brew install readline sqlite gdbm pkg-config
   2. brew install python
   3. Note: Mac OS X Lion comes with old version 2.7.1 of python (python --version) 
4. Set PATH in .bash_profile
   1. vim ~/.bash_profile
      1. export PATH=/usr/local/share/python:/usr/local/bin:$PATH
5. Create symlinks
   1. Within /(System/)?Library/Frameworks/Python.framework/Versions, sudo rm Current
   2. Within the above directories, ln -s /usr/local/Cellar/python/2.7.3 Current
6. Install pip, if necessary, using easy_install
   1. sudo easy_install pip
7. Using pip (sudo pip install [--upgrade] abc)
   1. Install nose
   2. Install numpy
   3. Install scipy with environmental variables settings
      1. sudo CC=clang CXX=clang FFLAGS=-ff2c pip install [--upgrade] scipy
   4. Install scikit-learn
   5. Install pandas
8. Install matplotlib
   1. Download source from repo: https://github.com/matplotlib/matplotlib
   2. cd ~Downloads/matplotlib-*
   3. python setup.py build
   4. python setup.py install
9. Install VW (Vowpal Wabbit)
   1. Install boost
      1. Download tar file
      2. mv boost extracted folder to /usr/local
      3. export BOOST_ROOT environmental variable
      4. cd to boost directory
      5. make and install
         1. sudo ./bootstrap
         2. sudo ./bjam install
      6. Download bjam
      7. mv to directory in PATH
         1. mv bjam /usr/local/bin
      8. Set bjam toolset to darwin
         1. bjam toolset=darwin stage
      9. Reference http://www.boost.org/doc/libs/1_41_0/more/getting_started/unix-variants.html#expected-build-output
   2. cd to VW directory
      1. make and test
         1. make
         2. make test