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Seminar on Internet Technologies (Winter 2017/2018): Difference between revisions
Seminar on Internet Technologies (Winter 2017/2018) (view source)
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|{{Hl2}} |'''Topic Advisor''' | |{{Hl2}} |'''Topic Advisor''' | ||
|{{Hl2}} |'''Initial Readings''' | |{{Hl2}} |'''Initial Readings''' | ||
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| '''Strengths and Limitations of Visualization Libraries for Data Science''' (partially practical) | |||
One core aspect of Data Science is data visualization. For this task, data scientists can exploit a plethora of different visualization libraries in different programming languages. | |||
The goal of this seminar topic is to work out advantages and disadvantages of each library and to show the key differences in practical examples based on a real-world dataset. | |||
Please note that students interested in this topic should be confident programmers in one of Python or R, and additionally in JavaScript, and ideally bring along some practical experience in data analysis/data mining. | |||
| [http://user.informatik.uni-goettingen.de/~dkoll David Koll] | |||
| [http://www.kdnuggets.com/2015/05/21-essential-data-visualization-tools.html] | |||
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| '''Transfer Learning for Visual Categorization''' | | '''Transfer Learning for Visual Categorization''' | ||