Sökning: "learning on demand"

Visar resultat 6 - 10 av 458 uppsatser innehållade orden learning on demand.

  1. 6. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskap

    Författare :Stella Jarlöv; Anton Svensson Dahl; [2023]
    Nyckelord :demand forecasting; data augmentation; time series data; machine learning; restaurant industry; generative adversarial networks; TimeGAN; XGBoost;

    Sammanfattning : This study aims to enhance the accuracy of a demand forecasting model, XGBoost, by incorporating synthetic multivariate restaurant time series data during the training process. The research addresses the limited availability of training data by generating synthetic data using TimeGAN, a generative adversarial deep neural network tailored for time series data. LÄS MER

  3. 7. Accelerating university-industry collaborations with MLOps : A case study about the cooperation of Aimo and the Linnaeus University

    Master-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Nico Pistor; [2023]
    Nyckelord :MLOps; Machine Learning Operations; Development Process; Machine Learning; Artificial Intelligence; DevOps; Collaboration;

    Sammanfattning : Many developed machine learning models are not used in production applications as several challenges must be solved to develop and deploy ML models. Manual reimplementation and heterogeneous environments increase the effort required to develop an ML model or improve an existing one, considerably slowing down the overall process. LÄS MER

  4. 8. Traffic State Estimation on Swedish Highways : Model Comparison using Multisource Data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jiaqi Xu; [2023]
    Nyckelord :Traffic State Estimation; Macroscopic Traffic Model; Extended Kalman Filter; Particle Filter; Data Fusion; Trafiklägesuppskattning; Makroskopisk trafikmodell; Utökad Kalman-filter; Partikelfilter; Datafusion;

    Sammanfattning : Due to the escalating demand for traffic information and management, the significance of traffic state estimation, which involves the assessment of traffic conditions on road segments with limited measurement data, is increasing. Two primary estimation methods are model-driven and data-driven. LÄS MER

  5. 9. Double Machine Learning for Insurance Price Optimization

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Jakob Kristiansson; [2023]
    Nyckelord :DML; Double Machine Learning; Price Optimization; Insurance Pricing; DML; Dubbel Maskininlärning; Prisoptimering; Försäkringsprissättning;

    Sammanfattning : This thesis examines how recent advances in debaised machine learning can be used for estimating price elasticities of demand within the automotive insurance field. Traditional methods such as generalized linear model (GLM) to estimate demand has no way of ensuring there are no biases in the underlying data selection, especially when the confounding variables are many. LÄS MER

  7. 10. Parents’ perceptions about preschool children’s use of mobile devices and experiences at art museums

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Sooyoun Kim; [2023]
    Nyckelord :preschool children; mobile devices; tablets; educational apps; child-computer interaction; art museums; museum learning;

    Sammanfattning : The child–environment interaction type, which involves touching and handling part of collections and displays, is less common in art museums. In addition, art museums demand many behavioural rules from their visitors. The adult caregivers, therefore, prefer that their preschool children participate in child-friendly activity programmes. LÄS MER