*Please note that the information in this section is provisional.

 

Software: Software tools/services to be used during the sessions and hands-on include:

  • Anaconda (https://www.anaconda.com/): Installation instructions for various platforms can be found at: https://docs.anaconda.com/anaconda/install/
    • Note: For Mac and Linux users, the system PATH must be updated after installation so that ‘conda’ can be used from the command line.
      • Mac OS X:
        • For bash users: export PATH=~/anaconda3/bin:$PATH
        • For csh/tcsh users: setenv PATH ~/anaconda3/bin:$PATH
      • Linux:
        • For bash users: export PATH=~/anaconda3/bin:$PATH
        • For csh/tcsh users: setenv PATH ~/anaconda3/bin:$PATH
      • It is recommend the above statement be put in the ~/.bashrc or ~/.cshrc file, so that it is executed every time a new terminal window is open.
      • To check that conda was installed, running “conda list” in the terminal should list all packages that come with Anaconda.
    • A number of tools and libraries that we will use can be configured from Anaconda: Python 3, NumPy, SciPy, Matplotlib, nltk, Jupyter Notebook, Ipython, Pandas, Scikit-learn and Seaborn.
    • For Deep Learning we will use PyTorch (https://pytorch.org): This can be installed from Anaconda, with ‘conda’ from the command line, the actual command line depends on the platform as follows: using the GUI on pytorch.org, choose the appropriate OS, conda, Python 3.6, CUDA None (for the examples the CPU version should suffice).
    • For Text Processing, SpaCy can be installed with ‘conda’ from the command line as shown at https://pypi.org/project/spacy
  • Neo4j (https://neo4j.com/): Installation and documentation can be found at https://neo4j.com/developer/get-started/ (we will likely use the online sandbox service provided at https://neo4j.com/sandbox-v2/, so no installation on local machines may be needed for experimenting with Neo4j).