ckt77/NYCU-Machine-Learning

NYCU 2024 Fall Machine Learning / 洪瑞鴻教授、邱維辰教授

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This repository provides comprehensive reference materials and code examples for students tackling machine learning assignments at NYCU. It helps students understand complex algorithms like Naive Bayes, K-Means, PCA, and LDA, using real-world datasets like images. The materials guide students through implementing these algorithms from scratch, explaining common pitfalls and solutions, and ultimately helping them earn good grades.

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Use this if you are a graduate student at NYCU taking the Machine Learning course and need detailed guidance, code examples, and explanations for your assignments.

Not ideal if you are a practitioner looking for a ready-to-use machine learning library or a general introduction to machine learning concepts without specific ties to the NYCU course curriculum.

academic-coursework machine-learning-education image-classification clustering-algorithms dimensionality-reduction
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Python

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Last pushed

Jan 05, 2025

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