LEARNING OBJECTS FOR STUDYING THE MATHEMATICAL FRAMEWORK OF MACHINE LEARNING CLASSIFICATION TECHNIQUES AND THEIR PERFORMANCE EVALUATION METRICS
A learning object (LO) is any educational resource intended to support students' study and learning. They are reusable and can incorporate text, graphics, animations, audio, and video. Based on the above, this work carried out the design and development of three LOs to guide those interested in the subject to understand the mathematical components of the KNN (K-Nearest Neighbors), Naïve Bayes, and SVM (Support Vector Machines) algorithms using Python as a coding platform and Jupyter Notebook pages containing text, graphics, and videos to enrich the learning experience.
LEARNING OBJECTS FOR STUDYING THE MATHEMATICAL FRAMEWORK OF MACHINE LEARNING CLASSIFICATION TECHNIQUES AND THEIR PERFORMANCE EVALUATION METRICS
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DOI: https://doi.org/10.22533/at.ed.153112401074
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Palavras-chave: Learning Objects, Machine Learning, SVM, KNN, Naive Bayes
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Keywords: Learning Objects, Machine Learning, SVM, KNN, Naive Bayes
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Abstract:
A learning object (LO) is any educational resource intended to support students' study and learning. They are reusable and can incorporate text, graphics, animations, audio, and video. Based on the above, this work carried out the design and development of three LOs to guide those interested in the subject to understand the mathematical components of the KNN (K-Nearest Neighbors), Naïve Bayes, and SVM (Support Vector Machines) algorithms using Python as a coding platform and Jupyter Notebook pages containing text, graphics, and videos to enrich the learning experience.
- Rubens Dias Rodrigues Junior
- Ivan Carlos Alcântara de Oliveira
