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Visual Analytics for Data Scientists
Participants to this module shall - Learn the principles and rules underlying the design of visual data representations and human-computer interactions - Understand,...-
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Efficiency - Effectiveness Trade-offs in Learning to Rank
This tutorial provides an 'Introduction to Learning to Rank' and focuses on 'Dealing with the Efficiency/Effectiveness trade-off in Web Search'. Moreover, it provides two...-
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GATE Course
The material is the 2017 version of a week-long training course delivered annually by the GATE team. Over almost ten years, this course has been developed to provide basic and...-
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Data Visualisation and Visual Analytics Module
This module provides an introduction to the concepts of vision and perception in order to design an effective data visualisation. Moreover, it provides insight into visual...-
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High Performance and Scalable Analytics Module
Mining with big data or big data mining has become an active research area. Running current analytical methodologies and software tools on a single personal computer cannot...-
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Interactive Learning Environments
King’s College London developed a variety of data science materials based on R and Python. R is a de facto standard in statistical computing and visualisation, while our... -
Archive Spark
An Apache Spark framework for easy data processing, extraction as well as derivation for archival collections. Originally developed for the use with Web archives, it has now... -
Archive Crawling
Web archives are typically very broad in scope and extremely large in scale. This makes data analysis appear daunting, especially for non-computer scientists. These... -
Jupyter Notebooks
King’s College London has developed complete stories around Jupyter Notebooks that form easy recipes for reproducible methods in social data science. Jupyter...-
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