InstallFest 2018

Fall 2018's kick-off event for the Data Science Initiative is a community #InstallFest. Come with your computer to this drop-in workshop to work on installing different pieces of software commonly used for research in and applying Data Science. Experts from the DSI, Library, IET, Center for Spatial Sciences, and more from across campus will be around to help you overcome install problems.

This is great opportunity to:

  • meet other students and researchers with similar interests,
  • find out about new software
  • troubleshoot installs on your machine
  • ask questions about how to get started with different software

Note that this event is focused on getting people over the hurdles in getting started with Data Science software. This is NOT intended as technical support for general computer issues or general support for a specific class and will not provided a guided overview on how to use a specific tool. Want to know more about a specific tool or technology and how to apply it to your research? Complete this form or send us an email to suggest a topic for a future workshop.

All members of the UC Davis community are welcome to attend. No registration is needed, but if you want to let us know you're coming you can do so [here]https://forms.library.ucdavis.edu/classes/descriptions.php#class217).

Examples of software include (but are not limited to):

  • Languages
    • R, RStudio & R packages
    • Python, numba, Anaconda
    • Stan
    • JavaScript
  • Tools for data cleaning
    • OpenRefine
  • Tools for collaboration and workflows * Open Science Framework * Jupyter notebooks * Text editors, plugins and customization * SSH and remote logins
  • Version control and reproducibility
    • Git, Bitbucket
    • Docker
  • Databases
    • MySQL Workbench, SQLite, NoSQL
    • Postgres
    • Solr
  • Virtual Machines and installing additional operating systems
  • Spatial tools & Geographical Information Systems
    • qGIS
    • PostGIS
    • Spatiallite
    • R & Python spatial libraries (raster, rgdal, etc.)
  • Machine learning & neural networks
    • TensorFlow
  • Data visualization * Tableau * ggplot in R
  • GPU toolkits
    • CUDA,
    • OpenCL
  • Development Tools
    • compilers
    • linkers
    • profilers
    • configure
    • make
    • cmake
  • Natural Language Processing
    • software and related Python/R packages (e.g., tm, rJava)
  • Social networks
    • R packages

We hope to see you there!