Olivia Guest

Nasa picture of LondonBy Olivia Guest, Software Sustainability Institute Fellow

The Open Data Science Conference, ODSC, was held for the first time in London on October 8th and 9th. As far as I understand, it has its roots in the US and has only recently expanded to another continent. I’m not sure what I expected as I was still very much recovering from PyCon UK (yes, I’m a lightweight). However, I had noticed that quite a few talks were on packages I and/or colleagues use (e.g., TensorFlow, scikit-learn, etc.) so I was excited to see how and what they’re used for  by others.

The first talk was delivered by Gaël Varoquaux, a core developer of scikit-learn, joblib, and other Python packages. He touched on a number of important issues. Firstly, he defined what a data scientist is as  the combination of statistics and code, and,…

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Research Data Visualisation WorkshopBy Raniere Silva, Community Officer, Olivia Guest, University of Oxford, Vincent Knight,Cardiff University, Christina Bergmann, Ecole Normale Supérieure.

The Institute’s Research Data Visualisation Workshop took place on the 28th of July 2016 at the University of Manchester. Raniere Silva’s warm welcome was followed by Prof. Jessie Kennedy’s, from the Institute for Informatics and Digital Innovation at Edinburgh Napier University, keynote talk. Jessie spoke about the miscommunication of data due to poor visualisation techniques and how to avoid it. With over 50 attendees, the workshop provided an environment for learning and sharing. In the following sections, we will cover the events that took place during the workshop.

The Keynote

RDVW keynote

The Research Data Visualisation keynote talk was titled: ‘…

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Postdoctoral Research Associate, Love Lab, Department of Experimental Psychology, University College London

Interests

For my postdoctoral work I am investigating the role of labels in categorisation, e.g., does labelling animals as “dogs” help children detect their commonalities? My interests are interdisciplinary, combining psychology, computer science, and neuroscience. I create computational models as a way of evaluating, instantiating, developing, and refining cognitive theories.

Research

Cognitive modelling aims to understand the nature of and relationship between the computational (the what), the algorithmic (the how), and the implementational (the physical substrate) levels. Framing questions about cognition using models leads to theory-testing and predictions/explanations. For these reasons, computational modelling plays a vital role in cognitive science.

My focus is on modelling how infants categorise. Specifically looking at the effect labels (i.e., words to denote category membership, e.g., “dog”) have on babies’ performance. Infants and adults can categorise stimuli often effortlessly using perceptual information and linguistic labels as input. For example, an infant can learn that the label “dog” denotes animals with fur, that bark, fetch sticks, have four legs, etc., by exposure to various types of dog. Thus they generalise “dog” to every animal that is a dog, but not to cats. Babies learn that certain labels apply to certain classes of things but not others.…

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