ML4T Software Installation

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

• IPython [link]
• A Python IDE, such as PyCharm or Spyder

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.