Fundamentals of Machine Learning · Digital lecture note

Lecture 7 – Feature selection, PCA, SVD, LDA and clustering

Makine Öğrenmesinin Temelleri – Feature selection, PCA, SVD, LDA ve kümeleme

Course: Fundamentals of Machine Learning (ELM472)
Semester: Semester 7 · Fall 2024–25
Format: PDF · 5 pages · 0.1 MB · handwriting-style LaTeX
Language: Turkish
Original note: Ders7.pdf

Open the PDF (0.1 MB)LaTeX source (.tex)Original handwritten note

Lecture 7 – Feature selection, PCA, SVD, LDA and clustering – first page of the digital lecture note

Notice: The digital notes were created from the handwritten notes with the help of Claude (Anthropic); they are meant as a supplementary resource and may contain errors. Always rely on the original notes and the official course materials.

What is in this note?

Section headings of the note (in Turkish):

1 Feature selection
Subset Selection
Principle Component analizi
Feature Embedding
Eigen faces
Singular value composition
Expectation maximization

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