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17 ta ish

Ish: Machine Learning Models for Identifying at-Risk Students: Applications and Challenges in Higher Education

  1. Support-Vector Networks

    Corinna Cortes, Vladimir Vapnik

    Maqola19955 iqtibos
    ABI

  2. Sarlavhasiz

    Boshqa4 iqtibos
    ABI

  3. ENOP: A Robust Methodology to Predict Working Employee Stress Levels Using Enhanced Neural Optimization Principle

    G. Ramkumar, B.Amarnath Reddy, R. Revathi +3

    Maqola20243 iqtibos
    ABI

  4. Deconstructing disengagement

    René F. Kizilcec, Chris Piech, Emily Schneider

    Maqola20132 iqtibos
    ABI

  5. Cluster-based distributed architecture for prediction of student’s performance in higher education

    L. Ramanathan, G Parthasarathy, K. Vijayakumar +2

    Maqola20182 iqtibos
    ABI

  6. An Error-Free and Reliable Data Communication Between People Using Human Body as a Network Medium

    G. Ramkumar, Sk. Rabbani Basha, D. Aruna +2

    Maqola20242 iqtibos
    ABI

  7. Mining Educational Data to Analyze Students Performance

    Brijesh Kumar, Saurabh Pal

    Maqola20112 iqtibos
    ABI

  8. Augmented Reality and AI in Higher Education: Creating Immersive Learning Experiences

    Faridakhon Tursunova, Nodima Oripova, Manzura Muhammadiyeva +3

    MaqolaIntelligent Tutoring Systems and Adaptive Learning20241 iqtibos
    ABI

  9. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  10. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  11. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  12. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  13. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  14. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  15. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  16. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  17. Sarlavhasiz

    Boshqa1 iqtibos
    ABI