Sökning: "Inlärnings metoder"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Inlärnings metoder.

  1. 1. Innovating the learning process in higher education throughthe integration of theory and practice in partnership with Industry and Students

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

    Författare :Daniel Anderson Mlabwa; Farhang Hajipour; [2022]
    Nyckelord :VUCA; Work-Integrated Learning; Knowledge-Economy; Learning Innovation; Paradigm Shift; Higher Education; Employability; Experiential Learning; VUCA Prime.;

    Sammanfattning : The VUCA (which stands for volatility, uncertainty, complexity, and ambiguity) conditions have overshadowed the national and global higher education systems, and social and economic systems are increasingly becoming dependent on knowledge and innovations. There is a call for the global higher education systems to attain a new set of quality standards (Waller et al. LÄS MER

  3. 2. Multi-Class Emotion Classification for Interactive Presentations : A case study on how emotional sentiment analysis can help end users better convey intended emotion

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

    Författare :Charlotte Andersson; [2022]
    Nyckelord :Interactive Presentations; Audience Engagement Platform; Emotion Prediction; Natural Language Processing; Text Classification; Sentiment Analysis; BERT; Case Study; Interaktiva Presenationer; Publikengagemangsplattform; Förutsägelse av Känslor; Natural Language Processing; Textklassificering; Attitydanalys; BERT; Fallstudie;

    Sammanfattning : Mentimeter is one of the fastest-growing startups in Sweden. They are an audience engagement platform that allows users to create interactive presentations and engage an audience. As online information spreads increasingly faster, methods of analyzing, understanding, and categorizing information are developing and improving rapidly. LÄS MER

  4. 3. Explainable Artificial Intelligence for Radio Resource Management Systems : A diverse feature importance approach

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

    Författare :Alexandru-Daniel Marcu; [2022]
    Nyckelord :Explainable artificial intelligence XAI ; Explainability pipeline; Feature importance; Kernel SHAP; CERTIFAI; Anchors; XAI in wireless systems; XAI for radio resource management; Förklarande artificiell intelligens XAI ; Förklarande pipeline; Prediktor betydelse; Kernel SHAP; CERTIFAI; Anchors; XAI i trådlösa system; XAI för radioresurshantering;

    Sammanfattning : The field of wireless communications is arguably one of the most rapidly developing technological fields. Therefore, with each new advancement in this field, the complexity of wireless systems can grow significantly. LÄS MER

  5. 4. Statistical Learning of Key Performance Indicators for Swedish Football

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Jonathan Forsberg; Edward Yu; [2022]
    Nyckelord :;

    Sammanfattning : Football is the indisputable most popular sport globally, and the central question within this game is how to become the winning outcoming part. A possible approach to answer this question is to utilise data and its information for analysis and provide keyperformance indicators that distinguish the successful from the unsuccessful teams. LÄS MER

  7. 5. Incorporating Metadata Into the Active Learning Cycle for 2D Object Detection

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

    Författare :Karsten Stadler; [2021]
    Nyckelord :Active learning; Deep Learning; Object detection; Metadata; Nuscenes Nuimages; Gaussian mixture model; Rejection sampling; Monte-Carlo methods; Aktiv Inlärning; Djupinlärning; Objektdetektering; metadata; Nuscenes Nuimages; Gaussisk blandingsmodell; Rejection sampling; Monte-Carlo metoder;

    Sammanfattning : In the past years, Deep Convolutional Neural Networks have proven to be very useful for 2D Object Detection in many applications. These types of networks require large amounts of labeled data, which can be increasingly costly for companies deploying these detectors in practice if the data quality is lacking. LÄS MER