Sökning: "Machine learning"

Visar resultat 1 - 5 av 304 avhandlingar innehållade orden Machine learning.

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

   Detta är en avhandling från Stockholm : KTH

   Författare :Fredrik Paulsson; KTH.; [2008]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

3. 2. Protein Model Quality Assessment A Machine Learning Approach

   Detta är en avhandling från Stockholm : Department of Biochemistry and Biophysics, Stockholm University

   Författare :Karolis Uziela; Stockholms universitet.; [2017]
   Nyckelord :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;

   Sammanfattning : 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). LÄS MER

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

   Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

   Författare :Zeeshan Khaliq; Uppsala universitet.; [2017]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

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

   Detta är en avhandling från Stockholm : Department of Computer and Systems Sciences, Stockholm University

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

   Sammanfattning : 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. LÄS MER

7. 5. Representation learning for natural language

   Detta är en avhandling från ; Chalmers tekniska högskola; Gothenburg

   Författare :Olof Mogren; [2018]
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; artificial neural networks; artificial intelligence; natural language processing; deep learning; machine learning; summarization; representation learning;

   Sammanfattning : Artificial neural networks have obtained astonishing results in a diverse number of tasks. One of the reasons for the success is their ability to learn the whole task at once (endto-end learning), including the representations for data. LÄS MER