Difference between revisions of "ML4T Software Installation"

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(Added overview and instructions)
(Separated instructions for each platform)
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'''Important note''': We use a specific, static dataset for this course, which we will provide. If you download your own data from Yahoo (or elsewhere), you will get wrong answers on assignments.
 
'''Important note''': We use a specific, static dataset for this course, which we will provide. If you download your own data from Yahoo (or elsewhere), you will get wrong answers on assignments.
  
== Instructions ==
+
== Required software ==
  
Install:
+
Install Python 2.7 (NOT Python 3) and the necessary libraries as instructed below for your favorite platform.
  
* Python 2.7 (NOT Python 3) [[http://docs.python-guide.org/en/latest/ link]]<br />
+
=== Linux ===
''If you're on Mac OS X, we recommend installing Python using [http://brew.sh/ Homebrew].''
 
* pip (in case your Python doesn't come with it) [[https://pip.pypa.io/en/latest/installing.html link]]
 
* virtualenv, virtualenvwrapper (highly recommended) [[http://docs.python-guide.org/en/latest/dev/virtualenvs/ link]]<br />
 
''Create a virtual environment to use for this course, and pip install the following within it.''
 
* IPython, NumPy 1.9+, SciPy 0.14+, Pandas 0.16+ [[http://docs.python-guide.org/en/latest/scenarios/scientific/ link]]
 
  
Test your environment by running the script: <tt>validate\_env.py</tt> (get it [https://s3.amazonaws.com/content.udacity-data.com/courses/ud501/assignments/01-HW2/validate_env.py here]).
+
* Install Python 2.7 [[http://docs.python-guide.org/en/latest/ link]]
 +
* Install pip (in case your Python doesn't come with it) [[https://pip.pypa.io/en/latest/installing.html link]]
 +
* Install virtualenv, virtualenvwrapper (highly recommended) [[http://docs.python-guide.org/en/latest/dev/virtualenvs/ link]]<br />
 +
** Create a virtual environment to use for this course:
 +
    $ mkvirtualenv ml4t
 +
    $ workon ml4t
 +
** And then pip install the following within it.
 +
* NumPy 1.9+, SciPy 0.14+, Pandas 0.16+ [[http://docs.python-guide.org/en/latest/scenarios/scientific/ link]]
  
    python validate_env.py
+
=== Mac OS X ===
  
If it complains, fix the problems, then repeat till you get a clean output (no errors or exceptions).
+
* Install Python 2.7 via Homebrew
 +
** If you don't have it already, first get [http://brew.sh/ Homebrew]
 +
** Then: <tt>brew install python</tt>
 +
* Install virtualenv, virtualenvwrapper (highly recommended) [[http://docs.python-guide.org/en/latest/dev/virtualenvs/ link]]<br />
 +
** Create a virtual environment to use for this course:
 +
    $ mkvirtualenv ml4t
 +
    $ workon ml4t
 +
** And then pip install the following within it.
 +
* NumPy 1.9+, SciPy 0.14+, Pandas 0.16+ [[http://docs.python-guide.org/en/latest/scenarios/scientific/ link]]
 +
 
 +
=== Windows ===
 +
 
 +
* Install Python 2.7 [[http://docs.python-guide.org/en/latest/ link]]
 +
* Install pip (in case your Python doesn't come with it) [[https://pip.pypa.io/en/latest/installing.html link]]
 +
* Install virtualenv, virtualenvwrapper (highly recommended) [[http://docs.python-guide.org/en/latest/dev/virtualenvs/ link]]<br />
 +
** Create a virtual environment to use for this course:
 +
    C:\Users\Monty> mkvirtualenv ml4t
 +
    C:\Users\Monty> workon ml4t
 +
** And then pip install the following within it.
 +
* NumPy 1.9+, SciPy 0.14+, Pandas 0.16+ [[http://docs.python-guide.org/en/latest/scenarios/scientific/ link]]
 +
 
 +
== Optional software ==
 +
 
 +
* IPython [[http://docs.python-guide.org/en/latest/scenarios/scientific/ link]]
 +
* A Python IDE, such as [https://www.jetbrains.com/pycharm/ PyCharm] or [https://pythonhosted.org/spyder/ Spyder]
 +
 
 +
== Data ==
 +
 
 +
TODO: Link to ML4T.zip
 +
 
 +
=== Test installation ===
 +
 
 +
Test your environment by running the script <tt>validate_env.py</tt> from the <tt>ML4T/</tt> directory. If it complains, fix the problems, then repeat.

Revision as of 11:27, 14 August 2015

Overview

Use the following instructions to set up a development environment on your local machine. It should include:

  • The proper version of Python (namely 2.7)
  • Installation of necessary libraries (e.g. NumPy, Pandas, etc.)
  • Installation of historical stock data.

Important note: We use a specific, static dataset for this course, which we will provide. If you download your own data from Yahoo (or elsewhere), you will get wrong answers on assignments.

Required software

Install Python 2.7 (NOT Python 3) and the necessary libraries as instructed below for your favorite platform.

Linux

  • Install Python 2.7 [link]
  • Install pip (in case your Python doesn't come with it) [link]
  • Install virtualenv, virtualenvwrapper (highly recommended) [link]
    • Create a virtual environment to use for this course:
   $ mkvirtualenv ml4t
   $ workon ml4t
    • And then pip install the following within it.
  • NumPy 1.9+, SciPy 0.14+, Pandas 0.16+ [link]

Mac OS X

  • Install Python 2.7 via Homebrew
    • If you don't have it already, first get Homebrew
    • Then: brew install python
  • Install virtualenv, virtualenvwrapper (highly recommended) [link]
    • Create a virtual environment to use for this course:
   $ mkvirtualenv ml4t
   $ workon ml4t
    • And then pip install the following within it.
  • NumPy 1.9+, SciPy 0.14+, Pandas 0.16+ [link]

Windows

  • Install Python 2.7 [link]
  • Install pip (in case your Python doesn't come with it) [link]
  • Install virtualenv, virtualenvwrapper (highly recommended) [link]
    • Create a virtual environment to use for this course:
   C:\Users\Monty> mkvirtualenv ml4t
   C:\Users\Monty> workon ml4t
    • And then pip install the following within it.
  • NumPy 1.9+, SciPy 0.14+, Pandas 0.16+ [link]

Optional software

Data

TODO: Link to ML4T.zip

Test installation

Test your environment by running the script validate_env.py from the ML4T/ directory. If it complains, fix the problems, then repeat.