Sökning: "Large data sets"

Visar resultat 1 - 5 av 372 avhandlingar innehållade orden Large data sets.

  1. 1. Data-driven AI Techniques for Fashion and Apparel Retailing

    Författare :Chandadevi Giri; Ulf Johansson; Jenny Balkow; Xianyi Zeng; Sebastien Thomessey; Maria Riveiro; Högskolan i Borås; []
    Nyckelord :SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; SAMHÄLLSVETENSKAP; NATURAL SCIENCES; SOCIAL SCIENCES; Digitalization; artificial intelligence; fashion and apparel industry; churn prediction; sales forecasting; campaign analysis; data driven AI decision-making; 数字化,人工智能,服装产业,客户流失预测,销售预测,竞争分析,数据驱动的人 工智能决策; Digitalisation; intelligence artificielle IA; industrie de la mode et de l habillement; prédiction de désabonnement; prévision des ventes; analyse des promotions; Prise de décision par IA axée sur les données; Digitalisering; Artificiell intelligens; Modeindustrin; Churnprediktion; Försäljningsprognoser; Kampanjanalys; Datadriven AI; Beslutsstöd; Business and IT; Handel och IT; Textil och mode generell ; Textiles and Fashion General ;

    Sammanfattning : Digitalisation allows companies to develop many new ways of interacting with customers and other stakeholders. These digital interactions typically generate data that can be stored and later processed for different objectives. LÄS MER

  2. 2. Patterns in big data bioinformatics : Understanding complex diseases with interpretable machine learning

    Författare :Mateusz Garbulowski; Jan Komorowski; Ryan J. Urbanowicz; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; complex diseases; big data; machine learning; transcriptomics; life sciences; rough sets; Bioinformatics; Bioinformatik;

    Sammanfattning : Alterations in the flow of genetic information may lead to complex diseases. Such changes are measured with various omics techniques that usually produce the so-called “big data”. Using interpretable machine learning (ML), we retrieved patterns from transcriptomics data sets. LÄS MER

  3. 3. Integrating multi-omics for type 2 diabetes : Data science and big data towards personalized medicine

    Författare :Klev Diamanti; Jan Komorowski; Claes Wadelius; Manfred Grabherr; Peter Spégel; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; NATURVETENSKAP; MEDICIN OCH HÄLSOVETENSKAP; NATURAL SCIENCES; MEDICAL AND HEALTH SCIENCES; type 2 diabetes; multi-omics; genomics; metabolomics; data science; machine learning; personalized medicine; Bioinformatics; Bioinformatik;

    Sammanfattning : Type 2 diabetes (T2D) is a complex metabolic disease characterized by multi-tissue insulin resistance and failure of the pancreatic β-cells to secrete sufficient amounts of insulin. Cells recruit transcription factors (TF) to specific genomic loci to regulate gene expression that consequently affects the protein and metabolite abundancies. LÄS MER

  4. 4. Data Driven Visual Recognition

    Författare :Omid Aghazadeh; Stefan Carlsson; Jiri Matas; KTH; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Visual Recognition; Data Driven; Supervised Learning; Mixture Models; Non-Parametric Models; Category Recognition; Novelty Detection;

    Sammanfattning : This thesis is mostly about supervised visual recognition problems. Based on a general definition of categories, the contents are divided into two parts: one which models categories and one which is not category based. We are interested in data driven solutions for both kinds of problems. LÄS MER

  5. 5. Dynamic Adaptations of Synchronization Granularity in Concurrent Data Structures

    Författare :Kjell Winblad; Konstantinos Sagonas; Erez Petrank; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; concurrent data structures; contention adapting; range queries; lock-freedom; adaptivity; linearizability; ordered sets; maps; key-value stores; concurrent priority queues; relaxed concurrent data structures; locks; delegation locking; Computer Science; Datavetenskap;

    Sammanfattning : The multicore revolution means that programmers have many cores at their disposal in everything from phones to large server systems. Concurrent data structures are needed to make good use of all the cores. Designing a concurrent data structure that performs well across many different scenarios is a difficult task. LÄS MER