data.washington.edu
UW Data Science Seminar | University of Washington
http://www.data.washington.edu/seminar/index.html
Analysis, Visualization and Discovery. The Data Science Seminar. Is a university-wide effort bringing together thought-leading speakers and researchers across campus to discuss topics related to data analysis, visualization and applications to domain sciences. The seminar is typically held on Wednesdays 3:30-4:30pm. Unless otherwise noted, the location for Fall Quarter 2016 is Johnson 075. All talks are free and open to the public. Computationally-Enabled Public Policy using Comprehensive Data. Communica...
realtimedecisions.com
20: Unstructured Data & Text Analytics - Real Time Decisions Webcast
http://www.realtimedecisions.com/20
Real Time Decisions Webcast. The world's leading podcast focused on practical solutions for business intelligence, analytics, and big data: the structure and function, theory and practice, art and science, present and future of business decision making – in real time, and at the right time. 20: Unstructured Data & Text Analytics. Http:/ media.blubrry.com/realtimedecisions/p/www.realtimedecisions.com/wp-content/uploads/rtdw020 unstructured data part1.mp3. Podcast: Play in new window. Much of what we handl...
machinelearningsalon.org
The Machine Learning Salon | What's New (Desktop)
http://www.machinelearningsalon.org/index.html
The Machine Learning Salon. The Machine Learning Salon. Provides free information about Machine Learning and Artificial Intelligence. Its aim is to develop the understanding of Machine Learning Theory and its applications by providing a first set of useful websites to people who are interested in Machine Learning. All descriptions are coming from the websites themselves. Pint of Science UK 2016. Explore attendance of the 320 events across the UK. Http:/ cs229.stanford.edu/materials.html. Http:/ www.w...
news.cs.washington.edu
UW CSE News
https://news.cs.washington.edu/page/2
Icelandic delicacy day at UW CSE. Inspired by the global nature of the Olympic games, the UW CSE Systems Group’s Icelandic Ph.D. students treated us to a lunch of treats from their homeland: fermented shark, smoked and salted foal meat, sheep’s head cheese, liver sausage, blood pudding, flat bread with smoked lamb and butter, sheep pate on rye bread, …. Michael Phelps may have won twenty two gold medals, but we bet he wouldn’t have been able to work his way through this stuff …. August 11, 2016. Demonstr...
macwright.org
Charts in 2015 - macwright.org
http://www.macwright.org/2015/07/10/charting-in-2015.html
Has a good idea. Unlike its many predecessors like HighCharts. That aimed to individually implement every chart type, d3 went a level down: giving users the fundamental tools they need to implement hundreds of unique graphics. This approach was wildly successful: it made d3 hard to outgrow, so professionals could write front-page graphics for newspapers with the same basic elements as beginners use to implement bar graphs. It’s been a while since I worked on a d3-centric project like iD. Were numerous an...
dabblingwithdata.wordpress.com
Do good and bad viz choices exist? – Dabbling with Data
https://dabblingwithdata.wordpress.com/2016/10/20/do-good-and-bad-viz-choices-exist
Do good and bad viz choices exist? October 20, 2016. October 26, 2016. Browsing the wonderful timeline of Twitter one evening, I noted an interesting discussion on subjects including Tableau Public, best practice, chart choices and dataviz critique. It’s perhaps too long to go into here, but this tweet from Chris Love. To summarise my POV: no good / bad viz choices. All should be promoted. Constructive critique should be welcomed not dismissed. Simples. Mdash; Chris Love (@ChrisLuv) October 19, 2016.
vis.stanford.edu
Stanford Vis Group | Termite: Visualization Techniques for Assessing Textual Topic Models
http://vis.stanford.edu/papers/termite
We moved to Seattle! We packed our bags and headed north to become the University of Washington Interactive Data Lab. Termite: Visualization Techniques for Assessing Textual Topic Models. Christopher D. Manning, Jeffrey Heer. The Termite system. A tabular view (left) displays term-topic distributions for an LDA topic model. A bar chart (right) shows the marginal probability of each term. PDF (2.3 MB). Termite: Visualization Techniques for Assessing Textual Topic Models. PDF (2.3 MB).
vis.stanford.edu
Stanford Vis Group | GraphPrism: Compact Visualization of Network Structure
http://vis.stanford.edu/papers/graphprism
We moved to Seattle! We packed our bags and headed north to become the University of Washington Interactive Data Lab. GraphPrism: Compact Visualization of Network Structure. Sanjay Kairam, Diana MacLean, Manolis Savva, Jeffrey Heer. GraphPrism facets and node-link diagram for the largest component of a network science co-authorship graph. PDF (2.1 MB). GraphPrism: Compact Visualization of Network Structure. Sanjay Kairam, Diana MacLean, Manolis Savva, Jeffrey Heer. PDF (2.1 MB).
vis.stanford.edu
Stanford Vis Group | Selecting Semantically-Resonant Colors for Data Visualization
http://vis.stanford.edu/papers/semantically-resonant-colors
We moved to Seattle! We packed our bags and headed north to become the University of Washington Interactive Data Lab. Selecting Semantically-Resonant Colors for Data Visualization. Julie Fortuna, Chinmay Kulkarni, Maureen Stone. PDF (481.6 KB). Selecting Semantically-Resonant Colors for Data Visualization. Julie Fortuna, Chinmay Kulkarni, Maureen Stone. Computer Graphics Forum (Proc. EuroVis). PDF (481.6 KB).
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