zhengyima/mnist-classification
Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）
This project helps students and beginners understand how different machine learning models classify handwritten digits. You input images of digits, and it shows you how various algorithms process and identify them. This is designed for anyone new to machine learning who wants to see core classification methods in action with a classic dataset.
444 stars. No commits in the last 6 months.
Use this if you are learning about machine learning and want to see practical examples of common classification algorithms working on image data.
Not ideal if you need a production-ready solution for digit recognition or want to classify images other than the MNIST dataset.
Stars
444
Forks
91
Language
Python
License
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Last pushed
Oct 16, 2020
Commits (30d)
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