872 search results for “machine learning” in the Public website
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Siuman Chung
Faculteit der Sociale Wetenschappen
s.chung@fsw.leidenuniv.nl | +31 71 527 3830
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Christine Espin
Faculteit der Sociale Wetenschappen
espinca@fsw.leidenuniv.nl | +31 71 527 6630
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Elise Swart
Faculteit der Sociale Wetenschappen
e.k.swart@fsw.leidenuniv.nl | +31 71 527 2727
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Marit Guda
Faculteit der Sociale Wetenschappen
m.c.guda@fsw.leidenuniv.nl | +31 71 527 6344
- About this minor
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Applied statistics as a pillar of data science
Data science is now growing fast in many places, but scholars at Leiden University have been developing data science techniques for a long time already. Thanks to their broad-based expertise, Leiden statisticians are currently combining the achievements in statistics with the latest methods of statistical…
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NWO subsidy for archaeological search engine: ‘There is no physical digging involved!’
When you want to analyse big quantities of archaeological data, you run into the issue that searching through excavation reports is extremely time-consuming. If only there existed a search engine specifically focused on querying these reports… But wait, work on an archaeological search engine focused…
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Exploring Deep Learning for Intelligent Image Retrieval
This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.
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LIC Lecture: Density functional theory in chemistry: Where are we today?
Lecture
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Reinforcement learning
The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.
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Data Science
The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.
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Blended learning
The programme is also offered in a blended learning version: this is a combination of distance learning and face-to-face learning. Read more information
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Algorithms for quantum software
Top scientists of three Dutch universities are working on software and systems for quantum computers. Researchers of the Leiden Institute of Advanced Computer Science (LIACS) and the Leiden Institute of Physics (LION) are developing new algorithms to make those super computers work. The coming years,…
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MacBERTh & GysBERT meet socio-linguistics: using machine learning to automate annotation and analysis in historical corpora
Lecture, Sociolinguistics series
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Learning tools
It is our goal to deliver a convenient, enjoyable, learning experience that goes beyond the basics. All of the apps are an initiative of the HANDS! Lab for Sign Languages and Deaf Studies at Leiden University, as part of the Language Socialization in Deaf Families project funded by the Leiden University…
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The Hybrid Intelligence Centre
Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. HI takes human expertise and intentionality into account when making meaningful decisions and perform appropriate actions, together with ethical, legal and societal values.…
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Self-directed learning with mobile technology in higher education
Language learners in higher education increasingly conduct out-of-class self-directed learning facilitated by mobile technology. This project aims to explore how university students use mobile technology for their self-directed language learning and investigate factors that influence their self-directed…
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Collaborative learning in teacher education: Intended, implemented and experienced curriculum
How is collaborative learning in teacher education designed and implemented? How do students experience those collaborative learning assignments? What aspects of the design and the implementation lead to which perceived learning outcomes?
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POST_SIGNATURE
To what extent is creative ownership in contemporary (graphic) design practices changing now that we are co-creating with machines? And can machines have copyrights, too?
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Language as a time machine
About 90 per cent of Austronesian and Papuan languages are under threat of soon becoming extinct. Marian Klamer is the only professor in the world who researches both these language groups. She records languages before they disappear and sheds new light on the history of Indonesia. Inaugural lecture…
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Student engagement in blended learning in higher education
In what way can teachers support and enlarge student engagement in a blended learning context?
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By Heritage Quest
Read all papers and other types of publication created by the project.
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Data Science: Computer Science (MSc)
The master's specialisation Data Science: Computer Science at Leiden University provides students thorough knowledge and understanding of statistical and computational aspects of data analysis, including their application in databases, advances in data mining, networks, pattern recognition, and deep…
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Computational Network Science Lab
The Leiden Computational Network Science Lab (CNS Lab) researches methods for knowledge discovery from real-world network data.
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Artificial Intelligence (MSc)
The master’s specialisation Artificial Intelligence offers future-oriented topics in computer science with a focus on machine learning, optimization algorithms, and decision support techniques.
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Ben van Werkhoven
Science
b.j.c.van.werkhoven@liacs.leidenuniv.nl | +31 71 527 2727
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Pingtao Ding
Science
p.ding@biology.leidenuniv.nl | +31 71 527 5306
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Thomas Bäck
Science
t.h.w.baeck@liacs.leidenuniv.nl | +31 71 527 7108
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Research in Physics, Classical/Quantum Information (MSc)
This master’s programme combines Physics with Data Science. You will learn how physics has its own tricks to deal with big data and how techniques from machine learning and deep learning can be applied to classical and quantum data. The first focus of attention is on classical data, including data mining,…
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University teachers’ learning paths during technological innovation of education
To what extent are university teachers' individual learning paths influenced by their teaching experience, motivation, and conceptions of teaching and learning through educational technology?
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Active Learning Network
The active learning network joins together everyone interested in the subject to move the theme further within Leiden University. The SALTSWAT pilot program researches the ways forward for Leiden University.
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Activating teaching and learning
The active learning ambition is based on the idea that knowledge is more likely to ‘stick’ when students are actively engaged with their learning and research. This active student participation has implications for how we teach: less consumption of knowledge and more efficient use of contact hours.
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Flexible learning pathways
The ambition to have flexible learning pathways is about creating possibilities to improve the content and form of students’ learning process, and to link learning to students’ needs. Students who have access to a flexible range of learning pathways can align their university career with their own personal…
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Data science
The majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…
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Object-based learning in science museums
How do museum visitors interpret the authenticity of museum objects? How can we support visitors' meaningful interactions with real objects?
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Bayesian uncertainty quantication in complex models
The aim of this project is to determine in which cases uncertainty statements resulting from a Bayesian statistical analysis can be trusted.
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Data Mining and Sports
Collecting data in sports increased in importance the last few years.
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Quantum Lab (aQa)
Quantum computing is a novel paradigm for computation, which is nearing real-world impact with the coming generation of limited, but nonetheless powerful quantum devices.
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Centre for Professional Learning
The Centre for Professional Learning (CPL) develops in-depth and challenging programmes for higher educated professionals.
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Neurogenomics of vocal learning
How does FoxP1 affect auditory perception on a behavioural and genomic level?
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Searching by Learning: Exploring Artificial General Intelligence on Small Board Games by Deep Reinforcement Learning
In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…
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Beth Lloyd
Faculteit der Sociale Wetenschappen
b.lloyd@fsw.leidenuniv.nl | +31 71 527 2727
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Dineke Tigelaar
ICLON
dtigelaar@iclon.leidenuniv.nl | +31 71 527 6552
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Wilfried Admiraal
ICLON
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Leiden Learning & Innovation Centre
LLInC supports innovative and high-quality education, within Leiden University and in partnership with academic and social organisations.
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Language Learning Resource Centre
The language learning resource centre unites all language teaching professionals working at Leiden University: teachers and researchers at the LUCL, ATC, LUCAS, LIAS, and ICLON.
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Learn to Dare!
The ‘Leer te Durven!’ program (Learn to Dare) is a preventive training program for children with mild anxiety symptoms (Simon & Bögels, 2014). The program has been developed for children between the ages of 8 and 12 who feel or behave anxiously, avoid situations, are afraid of doing things wrong, appear…
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Research
At Leiden University, researchers from all disciplines work together to find answers and design innovations in the field of artificial intelligence.
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Centre for Professional Learning
This page is currently only available in Dutch. Click here to view this page in Dutch.
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Statistical Science
The research programme Statistical Science is concerned with the analysis and interpretation of masses of data, the quantification of uncertainty using probability models, and the development and benchmarking of algorithms and methods with these aims.