Turing Tools, Practices and Systems Lightning Talks, May 2020
Creators: name: McInerny, Greg
name: Basiri, Ana
name: Löning, Markus
name: Gibson, Sarah
name: Dent, Chris
name: Clegg, Richard G.
Publisher: name: Zenodo
Year: 2020

description: <em><strong>Lightning talk presentations for the Turing's Tools, Practices and Systems Seminar on 27 May 2020</strong></em> <strong>WAYS that we are approaching user research</strong> (WAYS - What aren’t you seeing?) Investigated by: Greg McInerny, James Tripp, Daniela Szabluk, Marie Petrescu, Theo Damoulas, Natalie Thurlby, Joao Porto De Albuquerque Project website: https://www.turing.ac.uk/research/research-projects/visual-diagnostics-markov-chain-monte-carlo-mcmc GitHub: https://github.com/WarwickCIM/backfillz Additional link: www.warwick.ac.uk/cim <strong>Participatory Design of Participatory Platforms’ </strong> Investigated by: Ana Basiri, Nathanael Sheehan, Terry Lines, Nishit Biswas Website: https://www.indicativedatascience.com Twitter: @AnahidBasiri <strong>sktime: A Python Toolbox for Machine Learning with Time Series </strong> Investigated by: Markus Löning, Anthony Bagnall, Jason Lines, Franz J. Király, and many more … GitHub: https://github.com/alan-turing-institute/sktime Chat: https://gitter.im/sktime Website: https://alan-turing-institute.github.io/sktime Papers: Markus Löning and Franz Király (2020): “Forecasting with sktime”, arxiv.org/abs/2005.08067 Markus Löning et al. (2019): “sktime: A Unified Interface for Machine Learning with Time Series”, Workshop on Systems for ML at NeurIPS, learningsys.org/neurips19/sktime Anthony Bagnall et al. (2019): “A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency”, arxiv.org/abs/1909.05738 <strong>Project Binder</strong> Investigated by: Sarah Gibson, Kirstie Whitaker, <em>The Turing Way </em>team and the Jupyter Hubs team https://jupyterhub-team-compass.readthedocs.io/en/latest/team.html#jupyterhub-team GitHub: https://github.com/jupyterhub/binderhub Website: https://mybinder.readthedocs.io and https://mybinder.org Discourse: https://discourse.jupyter.org/c/binder Gitter: https://gitter.im/jupyterhub/binder Twitter: @mybinderteam <strong>Decision analysis for capital planning and public policy </strong> Investigated by: the Turing MUGM, ASG/TPS “Multiple Models”, and CDBB “Planning methodologies” teams led by Chris Dent Website: https://www.cdbb.cam.ac.uk/CDBBResearchBridgehead/Networks/2018Network_ComplexInfrastructure https://www.turing.ac.uk/research/research-projects/managing-uncertainty-government-modelling <strong>Raphtory: A practical system for the analysis of dynamic graphs </strong> Investigated by: Richard G. Clegg, Felix Cuadrado, Susan Grant-Muller, Imane Hafnaoui, Ben Steer GitHub: https://github.com/miratepuffin/raphtory Website: https://www.turing.ac.uk/research/research-projects/raphtory-practical-system-analysis-dynamic-graphs
description: This work was supported by The UKRI Strategic Priorities Fund under the EPSRC Grant EP/T001569/1, particularly the "Tools, Practices and Systems" theme within that grant, and by The Alan Turing Institute under the EPSRC grant EP/N510129/1.