Search for dissertations about: "machine learning"
Showing result 1 - 5 of 338 swedish dissertations containing the words machine learning.
-
1. Modularization of the Learning Architecture Supporting Learning Theories by Learning Technologies
University dissertation from Stockholm : KTHAbstract : This thesis explores the role of modularity for achieving a better adaptation of learning technology to pedagogical requirements. In order to examine the interrelations that occur between pedagogy and computer science, a theoretical framework rooted in both fields is applied. READ MORE
-
2. Using Learning Analytics to Understand and Support Collaborative Learning
University dissertation from Stockholm : Department of Computer and Systems Sciences, Stockholm UniversityAbstract : Learning analytics (LA) is a rapidly evolving research discipline that uses insights generated from data analysis to support learners and optimize both the learning process and learning environment. LA is driven by the availability of massive data records regarding learners, the revolutionary development of big data methods, cheaper and faster hardware, and the successful implementation of analytics in other domains. READ MORE
-
3. Understanding Complex Diseases and Disease Causative Agents The Machine Learning way
University dissertation from Uppsala : Acta Universitatis UpsaliensisAbstract : Diseases can be caused by foreign agents – pathogens – such as viruses, bacteria and other parasites, entering the body or by an internal malfunction of the body itself. The partial understanding of diseases like cancer and the ones caused by viruses, like the influenza A viruses (IAVs) and the human immunodeficiency virus, means we still do not have an efficient cure or defence against them. READ MORE
-
4. Manifold Learning in Computational Biology
University dissertation from Centre for Mathematical Sciences, Lund UniversityAbstract : This thesis deals with manifold learning techniques and their application in gene expression data analysis. Manifold learning is the study of methods that aim to infer geometrical structure from data sampled from manifolds, enabling nonlinear solutions to various machine learning tasks. READ MORE
-
5. Development and application of rule- and learning-based approaches within the scope of neuroimaging Tensor voting, tractography and machine learning
University dissertation from Stockholm : KTH Royal Institute of TechnologyAbstract : The opportunity to non-invasively probe the structure and function of different parts of the human body makes medical imaging an indispensable tool in clinical diagnostics and related fields of research. Especially neuroscientists rely on modalities like structural or functional Magnetic Resonance Imaging, Computed Tomography or Positron Emission Tomography to study the human brain in vivo. READ MORE
