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  1. 1
    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail

    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail by Ismail, Najihah

    Published 2021
    “…Python is an open source of programming software that conducted programming-based technique using the Scikit-Learn module to do the extraction of building from Land used land cover (LULC) and the result was 86.233% for overall accuracy. …”
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  2. 2
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Visual C++ object-oriented programming language was used to build the Intelligent Learning System for Turning. …”
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  3. 3
    Impact learning: A learning method from feature's impact and competition

    Impact learning: A learning method from feature's impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
    “…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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  4. 4
    Impact learning : A learning method from feature’s impact and competition

    Impact learning : A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
    “…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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  5. 5
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
    “…This project adapts the original MALESAbrain definitions and algorithm to create an intelligent learning tool; then, testing the tool in a students' meeting to discuss "To build up programming skills for computer science students, do you agree JAVA is a proper language in the first year foundation, course for computer science students"? …”
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  6. 6
    Intelligent Energy Management in Residential Building

    Intelligent Energy Management in Residential Building by Zubair, Nur Faizah

    Published 2014
    “…Some of the difficulty is the inefficient of energy management system in the building, but the biggest contribution to the deficiency is that there is no optimal algorithm which is suitable to the facilities in the building. …”
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    Final Year Project
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  7. 7
    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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  8. 8
    Impact learning: A learning method from feature’s impact and competition

    Impact learning: A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Muzahid, Abu Jafar Md, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
    “…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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  9. 9
    Tracking student performance in introductory programming by means of machine learning

    Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

    Published 2023
    Conference Paper
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  10. 10
    Poverty Classification of Central Perak Population Using Machine Learning

    Poverty Classification of Central Perak Population Using Machine Learning by P.Rajendran, Kumaran

    Published 2019
    “…In this study, back propagation algorithm and other machine learning algorithm will be used to build models via anaconda using python programming language that can classify each poor household appropriate their poverty status. …”
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  11. 11
    Current applications of machine learning in dentistry

    Current applications of machine learning in dentistry by Ghazali, Ahmad Badruddin, Reduwan, Nor Hidayah, Ibrahim, Roliana

    Published 2022
    “…ML programs can improve from experience automatically, unlike traditional computer programming, where every step of the program requires a written code (Mayo & Leung, 2018). …”
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  12. 12
    Smart Calculator 6.0

    Smart Calculator 6.0 by Andu, Yusrina, Mohamed, Nadiah, Othman, Norlida, Ahmad, Siti Noor Dina, Mohd Ruslan, Siti Zaharah, Jaafar, Zuraida

    Published 2025
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    Monograph
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  13. 13
    Community-based mosquito surveillance: an automatic mosquito-on-human-skin recognition system with a deep learning algorithm

    Community-based mosquito surveillance: an automatic mosquito-on-human-skin recognition system with a deep learning algorithm by Ong, Song-Quan, Gomesh Nair, Umi Kalsom Yusof, Hamdan Ahmad

    Published 2022
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  14. 14
    Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi

    Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi by Mohd Azmi, Amalin Aliesya

    Published 2023
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  15. 15
    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques

    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

    Published 2021
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  16. 16
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  17. 17
    ProCAss: An intelligent assessment for computer programming corpus

    ProCAss: An intelligent assessment for computer programming corpus by Zen, Kartinah, Tarmizi, Seleviawati, A.I, Dayang Nurfatimah, Din, Inson, Chua, Sui Soon

    Published 2005
    “…Then, the ability of LSA algorithm in grading computer program corpus will be evaluated.The grading process will not limited on certain programming languages, but on any programming languages.…”
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    Conference or Workshop Item
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  18. 18
    Enhancing professional development and training through AI for personalized learning: a framework to engaging learners / Zoel-Fazlee Omar ... [et al.]

    Enhancing professional development and training through AI for personalized learning: a framework to engaging learners / Zoel-Fazlee Omar ... [et al.] by Omar, Zoel-Fazlee, Mior Harun, Mior Harris, Mohd Ishar, Nor Irvoni, Mustapha, Nur Arfah, Ismail, Zurina

    Published 2024
    “…This paper explores the transformative potential of AI-driven personalized learning in enhancing professional development and training programs. …”
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  19. 19
    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim

    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim by Hamzah, Irni Hamiza, Ibrahim, Mohammad Nizam, Mohd Kasim, Linda

    Published 2006
    “…The selected neural network architecture is the Multilayer Perceptron (MLP) network, which is trained with three different types of learning algorithms, namely the Levenberg Marquardt (LM), Bayesian Regression (BR) and Gradient Descent (GDX). …”
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    Research Reports
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  20. 20
    A review on sentiment analysis model Chinese Weibo text

    A review on sentiment analysis model Chinese Weibo text by Dawei Wang, Rayner Alfred

    Published 2020
    “…For traditional machine learning, there are 2 mainly aspects of innovation: Simultaneous classifier (Adoboost+SVM) and Improvement of classical classification algorithm. …”
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