If it won't be simple, it simply won't be. [Hire me, source code] by Miki Tebeka, CEO, 353Solutions

Friday, September 07, 2012

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
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