Sökning: "performance comparison platform"

Visar resultat 1 - 5 av 137 uppsatser innehållade orden performance comparison platform.

  1. 1. Optimizing Flight Ranking:A Machine Learning Approach : Applying Machine Learning to Upgrade Flight Sorting and User Experience

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Habib Jabeli; [2024]
    Nyckelord :Machine Learning; Flight Comparison; Flygresor.se; Neural Networks; Flight Ranking; Random Forest; XGBoost;

    Sammanfattning : Flygresor.se, a leading flight comparison platform, uses machine learning to rankflights based on their likelihood of being clicked. The main goal of this project was toimprove this flight sorting to obtain a better user experience. The platform's existingmodel is based on a neural network approach and a limited set of features. LÄS MER

  3. 2. 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

  4. 3. Evaluating machine learning models for text classification

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

    Författare :Jonas Lilja; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : This thesis will explore the use of AWS machine learning services that enable natural language processing (NLP). More specifically, this work will focus on sentiment analysis of product and service reviews written in Swedish. LÄS MER

  5. 4. React Native vs. Flutter : A performance comparison between cross-platform mobile application development frameworks

    Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Gustav Tollin; Lidekrans Marcus; [2023]
    Nyckelord :React Native; Flutter; Android; Performance; Cross-platform; Mobile; Framework; CPU; Memory; FPS;

    Sammanfattning : This study compares the performance of two popular cross-platform mobile application development frameworks, Flutter and React Native. As the number of mobile users continues to grow, the ability to target multiple platforms using a single codebase is increasingly important for developers and companies. LÄS MER

  7. 5. Recommending digital books to children : Acomparative study of different state-of-the-art recommendation system techniques

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

    Författare :Malvin Lundqvist; [2023]
    Nyckelord :Recommendation Systems; Collaborative Filtering; Matrix Factorization; Multi-Layer Perceptron; Neural Network-based Collaborative Filtering; Implicit Feedback; Deep Learning; Term Frequency-Inverse Document Frequency; Rekommendationssystem; Kollaborativ filtrering; Matrisfaktorisering; Flerlagersperceptron; Neurala nätverksbaserad kollaborativ filtrering; Implicit data; Djupinlärning; Termfrekvens med omvänd dokumentfrekvens;

    Sammanfattning : Collaborative filtering is a popular technique to use behavior data in the form of user’s interactions with, or ratings of, items in a system to provide personalized recommendations of items to the user. This study compares three different state-of-the-art Recommendation System models that implement this technique, Matrix Factorization, Multi-layer Perceptron and Neural Matrix Factorization, using behavior data from a digital book platform for children. LÄS MER