Výsledky vyhledávání - Computer Science - Machine Learning

QAZAQAI – INTELLIGENT PLATFORM FOR COMPUTER SCIENCE EDUCATION WITH MACHINE LEARNING AND NLP

Autoři: Kundyz Maksutova Rozamgul Niyazova Manas Yergesh a další

Zdroj: Вестник Алматинского университета энергетики и связи. 2:90-99

A Data-Driven Framework Based on Machine Learning Approaches for Restructuring Computer Science Courses

Autoři: Ritika Awasthi Dr. Abhinav Shukla

Zdroj: International Journal of Environmental Sciences. 11:736-742

Integrating Computer Science into Biology: A Deep Learning Model for Bacterial Shape Classification in STEM Education

Autoři: Pakwalan Kiewwichai Pittayud Aursukitwattana

Zdroj: 2025 10th International STEM Education Conference (iSTEM-Ed). :1-5

Minimizing Student Failure with Machine Learning in Computer Science and Engineering Classes

Autoři: Kanika Sood Sachin Lodhi Rakesh Mahto

Zdroj: 2025 International Conference on Circuit, Systems and Communication (ICCSC). :1-8

Optimization of Artificial Intelligence (AI) and Machine Learning (ML) Integration in Modern Computer Science: A TOPSIS-based Analysis

Zdroj: REST Journal on Data Analytics and Artificial Intelligence. 3:15-27

A Comparative Review of Machine Learning and Computer Science Techniques for Optimising Healthcare Management Systems

Autoři: Deepak Sharma Jitendra Kanungo Narendra Singh a další

Zdroj: New Horizons of Science, Technology and Culture Vol. 4 ISBN: 9788199170322

Periodontal Disease Detection with Machine Learning Technology From Radiographic Images : An Interdisciplinary Study Of Dentistry and Computer Science

Autoři: Yusra Fadhillah Ade Ismail Abdul Kodir Muhammad Noor Hasan Siregar

Zdroj: CHIPSET, Vol 5, Iss 02 (2024)

Témata: Machine Learning, TK7885-7895, QA76.75-76.765, Computer engineering. Computer hardware, Periodontal, Image Classification, Neural Network, Toot Detection, Convolutional, Computer software

Přístupová URL adresa: https://doaj.org/article/ece5e6b3789c4929ab5d9b0915532792

STEM Workshops and Students’ Interest in Mathematics, Physics, and Computer Science: Machine Learning Approach.

Autoři: Milenković, Aleksandar Ostojić, Dragutin Rajković, Dalibor a další

Zdroj: International Journal of Instruction. Jan2026, Vol. 19 Issue 1, p367-386. 20p.

Témata: STEM education, Mathematics, Physics, Student engagement, Sociodemographic factors, Computer science, Student interests, Machine learning

A Deep Learning Approach for Multiclass Domain-Specific Question Classification in Computer Science for Bangla Language

Autoři: Md. Nihad Hossain Dip Karmakar Prapti Nandi a další

Zdroj: 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE). :1-6

Generative AI with ensemble machine learning framework for computer science graduates employability prediction using educational big data

Autoři: Jaiteg Singh Ruchi Mittal Vikas Rattan

Zdroj: International Journal of Computing and Digital Systems. 18:1-19

End-to-end data quality-driven framework for machine learning in production environment

Autoři: Bayram, Firas Ahmed, Bestoun S. Hallin, Erik

Zdroj: Heliyon. 12(1)

Témata: Data quality, Data-driven AI, Drift detection, Machine learning, MLOps, Computer Science, Datavetenskap

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-108182
https://doi.org/10.1016/j.heliyon.2025.e44416

Unveiling Career Pathways: Success and Challenges of Bangladeshi Women in Computer Science Through Machine Learning

Autoři: Md. Azim Howlader Fahad Bin Aziz Mahbuba Yesmin Turaba a další

Zdroj: Journal of Innovation and Technology. 2025

Deep Learning Approaches for Intelligent Intrusion Detection Systems: Bridging Computer Science and Cybersecurity

Autoři: Nasir Abbas

Evaluation of computer network data security based on a deep learning algorithm

Autoři: Ma Sujing Sun Xinghua

Zdroj: Journal of Intelligent Systems, Vol 34, Iss 1, Pp 1462-74 (2025)

Témata: network data security, deep learning, open computer, artificial intelligence, Science, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2191-026X

Přístupová URL adresa: https://doaj.org/article/e88a1fa43a2a42d19c991985a44e97cd

Integrating Machine Learning and Artificial Intelligence for Next-Generation Cybersecurity in Computer Science Applications

Autoři: Naveed Akhtar

How Do Computer Science Students Perceive Self-Study with Open-Source Repositories for Building AI/ML Systems?

Autoři: Azamnouri, Aidin Koch, Nadine Nicole Bogner, Justus a další

Zdroj: 2025 IEEE/ACM 37th International Conference on Software Engineering Education and Training (CSEE&T). :376-381

Témata: Machine Learning, AI Engineering, Computer Science Students, Artificial Intelligence, Open-source Repositories, Project-based Learning, Self-study

ON INTEGRATED TRAINING OF FUTURE TEACHERS OF COMPUTER SCIENCE ON THE BASIS OF STEM EDUCATION AND MACHINE LEARNING

Autoři: Meruyert Serik Nurzhanar Karilkhan

Zdroj: ICERI Proceedings. 1:10861-10865

Large Language Models in Computer Science Education: A Systematic Literature Review

Autoři: Nishat Raihan Mohammed Latif Siddiq Joanna C.S. Santos a další

Zdroj: Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1. :938-944

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Human-Computer Interaction, Machine Learning (cs.LG), Human-Computer Interaction (cs.HC)

Přístupová URL adresa: http://arxiv.org/abs/2410.16349

Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model

Autoři: Hans Moen Vishnu Raj Andrius Vabalas a další

Přispěvatelé: Hans Moen Vishnu Raj Andrius Vabalas a další

Zdroj: Moen, H, Raj, V, Vabalas, A, Perola, M, Kaski, S, Ganna, A & Marttinen, P 2024, ' Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model ', arXiv.org . https://doi.org/10.48550/arXiv.2412.08873

Témata: Computer Science - Machine Learning, EHR, Computer Science - Artificial Intelligence, Transformers, Deep learning, Disease prediction, Longitudinal health trajectories

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2412.08873
https://research.manchester.ac.uk/en/publications/430d6c6a-f37c-436a-aecd-fb7c3174f857
https://doi.org/10.48550/arXiv.2412.08873
https://aaltodoc.aalto.fi/handle/123456789/139226

HardML: A Benchmark for Evaluating Data Science and Machine Learning Knowledge and Reasoning in AI

Autoři: Tidor-Vlad Pricope

Zdroj: Studia Universitatis Babes-Bolyai: Series Informatica, Vol 69, Iss 2 (2025)

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Large Language Models, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Electronic computers. Computer science, Multiple Choice Benchmark, NLP Benchmarks, Evaluation of AI Systems, QA75.5-76.95, Machine Learning Education, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2501.15627
https://doaj.org/article/0ccddf3fb3a848deabb20dfc10779650