Search for dissertations about: "Machine Learning"

Showing result 1 - 5 of 332 swedish dissertations containing the words Machine Learning.

  1. 1. Modularization of the Learning Architecture Supporting Learning Theories by Learning Technologies

    University dissertation from Stockholm : KTH

    Author : Fredrik Paulsson; KTH.; [2008]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Computer Science; Technology Enhanced Learning; e-learning; Semantic Web; Service Orientation; Learning Object; Virtual Learning Environment; TECHNOLOGY Information technology Computer science; TEKNIKVETENSKAP Informationsteknik Datavetenskap;

    Abstract : 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. 2. Protein Model Quality Assessment A Machine Learning Approach

    University dissertation from Stockholm : Department of Biochemistry and Biophysics, Stockholm University

    Author : Karolis Uziela; Stockholms universitet.; [2017]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Protein Model Quality Assessment; structural bioinformatics; machine learning; deep learning; support vector machine; proq; Artificial Neural Network; protein structure prediction; biokemi med inriktning mot bioinformatik; Biochemistry towards Bioinformatics;

    Abstract : Many protein structure prediction programs exist and they can efficiently generate a number of protein models of a varying quality. One of the problems is that it is difficult to know which model is the best one for a given target sequence. Selecting the best model is one of the major tasks of Model Quality Assessment Programs (MQAPs). READ MORE

  3. 3. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining

    University dissertation from Karlskrona : Blekinge Tekniska Högskola

    Author : Eva García-Martín; Blekinge Tekniska Högskola.; [2020]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; machine learning; energy efficiency; data stream mining; green machine learning; edge computing;

    Abstract : Energy efficiency in machine learning explores how to build machine learning algorithms and models with low computational and power requirements. Although energy consumption is starting to gain interest in the field of machine learning, still the majority of solutions focus on obtaining the highest predictive accuracy, without a clear focus on sustainability. READ MORE

  4. 4. Understanding Complex Diseases and Disease Causative Agents The Machine Learning way

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Zeeshan Khaliq; Uppsala universitet.; [2017]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Pathogens; Influenza A viruses; Human immunodeficiency virus; Simian immunodeficiency virus; Pathogenicity; Cancer; long noncoding RNAs; Machine learning; Host specificity; Host-specific signatures; Bioinformatics; Bioinformatik;

    Abstract : 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

  5. 5. Using Learning Analytics to Understand and Support Collaborative Learning

    University dissertation from Stockholm : Department of Computer and Systems Sciences, Stockholm University

    Author : Mohammed Saqr; Stockholms universitet.; [2018]
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Learning analytics; Social Network Analysis; Collaborative Learning; Medical Education; Interaction Analysis; Machine Learning; informationssamhället; Information Society;

    Abstract : 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