GithubHelp home page GithubHelp logo

ssyoon / 2017-summer-workshop Goto Github PK

View Code? Open in Web Editor NEW

This project forked from data-on-the-mind/2017-summer-workshop

0.0 1.0 0.0 30.86 MB

Exercises, data, and more for our 2017 summer workshop (funded by the Estes Fund and in partnership with Project Jupyter and Berkeley's D-Lab)

HTML 49.43% Jupyter Notebook 41.53% Python 2.61% CSS 0.43% JavaScript 4.95% Smarty 0.02% Shell 0.01% R 0.71% Makefile 0.16% Batchfile 0.15%

2017-summer-workshop's Introduction

Data on the Mind 2017 Workshop

Dates: June 26-29, 2017
Website: http://www.dataonthemind.org/2017-workshop
Schedule: http://www.dataonthemind.org/2017-workshop/schedule
Video stream: https://www.youtube.com/playlist?list=PLKW2Azk23ZtSOUnLafEn0W1FEf-Rw-8pi

Tackling the new data frontier

Big data and naturally occurring datasets (NODS) are increasingly of interest to cognitive scientists and psychologists. With the proper tools and mindset, these data can provide compelling evidence of human behavioral, cognitive, and social process in natural settings. Big data and NODS present an unprecedented opportunity to explore theory-driven questions -- questions rooted in theories developed in rigorous lab studies -- in real-word datasets. These naturalistic explorations can generate new ideas that can be further refined in follow-up lab studies, creating a virtuous cycle of theory development.

However, along with this unique opportunity comes unique challenges. Graduate students and postdoctoral researchers in cognitive science and psychology have often been trained to collect and handle data that are relatively small and that come from tightly controlled lab settings. Although early-career scientists have deep theoretical knowledge of their research areas that would be powerfully applied to big data and NODS, many lack experience dealing with the challenges posed by these messier (and often exponentially larger) datasets, including analysis selection, computational capacity, and data collection.

Our (free) 2017 workshop

To help cognitive scientists and psychologists tackle these issues, Data on the Mind has been funded by the Estes Fund to create a 4-day workshop of hands-on introductions to topics that are essential for theory-driven research using big data and NODS. Each tutorial is taught by an expert in that area and will include real code and other exercises that will empower participants to immediately apply these techniques to their own research.

Join in remotely with our free live stream

While we're no longer accepting applications for the in-person event, we are excited to announce that we will also be publicly broadcasting the event live via YouTube (at no cost). After the workshop, we'll be converting the broadcast into a series of online tutorials—all of which will also be posted for free on YouTube after the event. All workshop materials will also be made available for free to remote participants during the event and will be released publicly after the event.

For more, head over to our website: http://www.dataonthemind.org/2017-workshop/live-stream

Videos

Tune in using the YouTube channel for the Berkeley Institute for Data Science: https://www.youtube.com/playlist?list=PLKW2Azk23ZtSOUnLafEn0W1FEf-Rw-8pi

Server

You'll need to complete our registration form (on our live stream website) to get access. (Please note that this process is not automated and must be approved by the workshop instructors. As a result, it may take some time before your registration is approved. We highly recommend that you register at least several hours before the workshop that you're interested in attending.)

Once you've registered, you should receive an email with your account information. You can log in on the JupyterHub server's website with your account information at this website: http://bit.ly/dotm-workshop

The first time that you access the server, you'll also need to pull the GitHub repository with the workshop materials:

  1. In the top right-hand corner of the main JupyterHub screen, click on the "New" drop-down menu.
  2. Select "Terminal" from the menu.
  3. When you're in the new tab with the terminal window, paste this into the command line: git clone https://github.com/Data-on-the-Mind/2017-summer-workshop/
  4. Press enter.
  5. Wait for it to say Checking connectivity... done.
  6. Close the terminal tab.

That's it! Again, you'll only need to do these steps the first time you log in.

Scope of the workshop

This workshop will rely on programming in both R and Python, and tutorials will assume that all participants will start out with at least a beginner's level of programming in both languages. All tutorials should be accessible to anyone with a beginner's level of programming in R and Python. Check out our list of tutorials here: http://www.dataonthemind.org/2017-workshop/schedule

Pleaes keep in mind that we will not be covering any introductions to basic programming in our workshop, so be sure to complete some basic R and/or Python tutorials before attending in person or remotely. We link to some free online basic programming tutorials here: http://www.dataonthemind.org/2017-workshop/introductions-r-and-python

Questions?

Contact Alex Paxton at <paxton [dot] alexandra [at] berkeley [dot] edu>.

Organizing committee

  • Tom Griffiths (University of California, Berkeley)
  • Alexandra Paxton (University of California, Berkeley)
  • Michael C. Frank (Stanford University)
  • Todd Gureckis (New York University)

Our funding partners

We'd like to thank our funding partners who made this possible:

2017-summer-workshop's People

Contributors

a-paxton avatar aculich avatar alexanderrich avatar arotto avatar davevinson avatar gabedoyle avatar gureckis avatar henchc avatar jhamrick avatar mcfrank avatar singmann avatar suchow avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.