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Pattern-Recognition-Fashion-MNIST

About Data

This lab aims to classify fashion items from the Fashion-MNIST dataset using Logistic Regression (LR) and Support Vector Machine (SVM). Fashion-MNIST consists of 70,000 images (28x28 pixels) belonging to 10 fashion categories. In addition to building models, the lab also explores the "Curse of Dimensionality" and applies PCA/LDA for feature reduction, analyzing their impact on model performance.

Project Structure

Folder Description
dataset Contains the original dataset used for training and testing.
report Documented reports and presentations summarizing the project findings.
set_up Contains the environment setup files and dependencies required to run.

Contributors

Name Major University
Kieu Thi Ngoc Vui Data Science University of Science (VNUHCM)
Nguyen Ngoc Thanh Thu Data Science University of Science (VNUHCM)
Phan Binh Phuong Data Science University of Science (VNUHCM)
Huynh Thao Quynh Data Science University of Science (VNUHCM)
Ly Vinh Thuan Data Science University of Science (VNUHCM)
Nguyen Tran Le Hoang Data Science University of Science (VNUHCM)
Nguyen Thuan Phat Data Science University of Science (VNUHCM)
Duong Thanh Phong Data Science University of Science (VNUHCM)

Git Commit Message Rule

After performing the git add . command, the git commit message should follow this structure:

git commit -m "[folder/file updated] - [task description]"

Example:

git commit -m "Fashion_MNIST_Classifier/ItemClassification.ipynb - Reducing dimensions using PCA."

Task description should provide enough information for other members to understand what was updated or changed, e.g., fixing bugs, adding features, refactoring code.

After that, use the git push command to push into the GitHub repository.

About

Classify items from the Fashion-MNIST dataset using Logistic Regression (LR) and Support Vector Machine (SVM) models.

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  • Jupyter Notebook 100.0%