Editing Human Centered Data Science (Fall 2018)/Schedule
From CommunityData
Warning: You are not logged in. Your IP address will be publicly visible if you make any edits. If you log in or create an account, your edits will be attributed to your username, along with other benefits.
The edit can be undone. Please check the comparison below to verify that this is what you want to do, and then publish the changes below to finish undoing the edit.
Latest revision | Your text | ||
Line 224: | Line 224: | ||
[[HCDS_(Fall_2018)/Day_6_plan|Day 6 plan]] | [[HCDS_(Fall_2018)/Day_6_plan|Day 6 plan]] | ||
[[:File:HCDS | <!-- [[:File:HCDS Week 6 slides.pdf|Day 6 slides]] --> | ||
;Interrogating algorithms: ''algorithmic fairness, transparency, and accountability; methods and contexts for algorithmic audits'' | ;Interrogating algorithms: ''algorithmic fairness, transparency, and accountability; methods and contexts for algorithmic audits'' | ||
Line 268: | Line 268: | ||
=== Week 7: November 8 === | === Week 7: November 8 === | ||
[[HCDS_(Fall_2018)/Day_7_plan|Day 7 plan]] | [[HCDS_(Fall_2018)/Day_7_plan|Day 7 plan]] | ||
;Critical approaches to data science: ''power, data, and society; ethics of crowdwork'' | ;Critical approaches to data science: ''power, data, and society; ethics of crowdwork'' | ||
Line 305: | Line 303: | ||
[[HCDS_(Fall_2018)/Day_8_plan|Day 8 plan]] | [[HCDS_(Fall_2018)/Day_8_plan|Day 8 plan]] | ||
[[:File:HCDS | <!-- [[:File:HCDS Week 8 slides.pdf|Day 8 slides]] --> | ||
;Human-centered algorithm design: ''algorithmic interpretibility; human-centered methods for designing and evaluating algorithmic systems'' | ;Human-centered algorithm design: ''algorithmic interpretibility; human-centered methods for designing and evaluating algorithmic systems'' | ||
Line 368: | Line 366: | ||
[[HCDS_(Fall_2018)/Day_10_plan|Day 10 plan]] | [[HCDS_(Fall_2018)/Day_10_plan|Day 10 plan]] | ||
[[:File:HCDS | <!-- [[:File:HCDS Week 10 slides.pdf|Day 10 slides]] --> | ||
;User experience and big data: ''Design considerations for machine learning applications; human centered data visualization; data storytelling'' | ;User experience and big data: ''Design considerations for machine learning applications; human centered data visualization; data storytelling'' | ||
Line 387: | Line 385: | ||
;Resources | ;Resources | ||
* | * Megan Risdal, ''[http://blog.kaggle.com/2016/06/29/communicating-data-science-a-guide-to-presenting-your-work/ Communicating data science: a guide to presenting your work].'' Kaggle blog, 2016. | ||
* | * Marilynn Larkin, ''[https://www.elsevier.com/connect/how-to-give-a-dynamic-scientific-presentation How to give a dynamic scientific presentation].'' Elsevier Connect, 2015. | ||
* Bart P. Knijnenburg, Martijn C. Willemsen, Zeno Gantner, Hakan Soncu, and Chris Newell. 2012. ''[https://pure.tue.nl/ws/files/3484177/724656348730405.pdf Explaining the user experience of recommender systems].'' User Modeling and User-Adapted Interaction 22, 4-5 (October 2012), 441-504. DOI=http://dx.doi.org/10.1007/s11257-011-9118-4 | * Bart P. Knijnenburg, Martijn C. Willemsen, Zeno Gantner, Hakan Soncu, and Chris Newell. 2012. ''[https://pure.tue.nl/ws/files/3484177/724656348730405.pdf Explaining the user experience of recommender systems].'' User Modeling and User-Adapted Interaction 22, 4-5 (October 2012), 441-504. DOI=http://dx.doi.org/10.1007/s11257-011-9118-4 | ||
* Megan Risdal, ''[http://blog.kaggle.com/2016/08/10/communicating-data-science-why-and-some-of-the-how-to-visualize-information/ Communicating data science: Why and how to visualize information].'' Kaggle blog, 2016. | * Megan Risdal, ''[http://blog.kaggle.com/2016/08/10/communicating-data-science-why-and-some-of-the-how-to-visualize-information/ Communicating data science: Why and how to visualize information].'' Kaggle blog, 2016. | ||
* Megan Risdal, ''[http://blog.kaggle.com/2016/06/13/communicating-data-science-an-interview-with-a-storytelling-expert-tyler-byers/ Communicating data science: an interview with a storytelling expert].'' Kaggle blog, 2016. | * Megan Risdal, ''[http://blog.kaggle.com/2016/06/13/communicating-data-science-an-interview-with-a-storytelling-expert-tyler-byers/ Communicating data science: an interview with a storytelling expert].'' Kaggle blog, 2016. | ||
* Richard Garber, ''[https://joyfulpublicspeaking.blogspot.com/2010/08/power-of-brief-speeches-world-war-i-and.html Power of brief speeches: World War I and the Four Minute Men].'' Joyful Public Speaking, 2010. | |||
* Brent Dykes, ''[https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/ Data Storytelling: The Essential Data Science Skill Everyone Needs].'' Forbes, 2016. | * Brent Dykes, ''[https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/ Data Storytelling: The Essential Data Science Skill Everyone Needs].'' Forbes, 2016. | ||
* Xavier Amatriain and Justin Basilico. ''[https://medium.com/netflix-techblog/netflix-recommendations-beyond-the-5-stars-part-1-55838468f429 Netflix Recommendations: Beyond the 5 stars].'' Netflix Tech Blog, 2012. | |||
*Fabien Girardin. ''[https://medium.com/@girardin/experience-design-in-the-machine-learning-era-e16c87f4f2e2 Experience design in the machine learning era].'' Medium, 2016. | |||
* Chen, N., Brooks, M., Kocielnik, R., Hong, R., Smith, J., Lin, S., Qu, Z., Aragon, C. ''[https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1254&context=hicss-50 Lariat: A visual analytics tool for social media researchers to explore Twitter datasets].'' Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS), Data Analytics and Data Mining for Social Media Minitrack (2017) | |||
<br/> | <br/> | ||
<hr/> | <hr/> | ||
Line 423: | Line 417: | ||
;Homework assigned | ;Homework assigned | ||
* | * none! | ||
;Resources | ;Resources |