This repo contains datasets and Machine Learning
tasks/solutions related the the Machine Learning
workshop.

HOW TO WORK HERE (ACTION ITEMS):

1) Please create a SEPARATE BRANCH for >>yourself<<
   and name it whatever you like.

2) If you need to commit your solution to the repo,
   please do it in
          *) YOUR BRANCH, not in the master,
          *) subfolder of relevant workshop folder.

   e.g. for John Smith:
        <branch jsmith>
        PROJECT_ROOT/workshop2/jsmith/mycoolsolution1.py
        PROJECT_ROOT/workshop2/jsmith/mycoolsolution2.py

3) If you need to commit new data to the dataset,
   please do it on MASTER BRANCH, to make your examples
   be available to everyone.

4) If you have some reasonable and valuable improvement
   for the whole project, please feel free to merge it
   to the MASTER BRANCH after getting approval from majority
   of participants.

REQUIREMENTS:
    # numpy to be installed (for vectorized computations)
    sudo pip install numpy

    # matplotlib to be installed (for plotting the data)
    sudo pip install matplotlib

    # h5py to be installed (for H5 files support,
    # which are designed to store nonuniform
    # data structures, like various data-sets)
    sudo pip install h5py

    # [optional] pyinstaller to be installed (for standalone
    # python scripts executables)
    # NOTE: you don't install pyinstaller, then
    #	do not set GENERATE_PYTHON_STANDALONE_EXECUTABLES
    #   CMake parameter to True.
    sudo pip install pyinstaller

FOR CONVENIENCE:

* You can add custom run procedures in your IDE, to
  make it convenient to start relevant python script
  directly from IDE.