{"id":25369965,"url":"https://github.com/tschechlovdev/kmeans_mnist","last_synced_at":"2026-05-07T13:01:56.875Z","repository":{"id":229991402,"uuid":"778151430","full_name":"tschechlovdev/kmeans_MNIST","owner":"tschechlovdev","description":"Demonstration of using k-Means to cluster images of handwritten digits (MNIST dataset). Source Code for corresponding article on Medium.","archived":false,"fork":false,"pushed_at":"2024-03-27T11:02:14.000Z","size":127,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-26T16:41:20.460Z","etag":null,"topics":["clustering","image-dataset","python","scikit-learn"],"latest_commit_sha":null,"homepage":"https://medium.com/@tschechd/k-means-clustering-on-image-data-using-the-mnist-dataset-8101fcc650eb","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tschechlovdev.png","metadata":{"files":{"readme":"Readme.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2024-03-27T07:13:53.000Z","updated_at":"2025-02-08T17:04:22.000Z","dependencies_parsed_at":"2024-03-27T09:26:45.936Z","dependency_job_id":"c2cd8b3a-4b08-430d-b255-bcc6756d07d6","html_url":"https://github.com/tschechlovdev/kmeans_MNIST","commit_stats":null,"previous_names":["tschechlovdev/kmeans_mnist"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/tschechlovdev/kmeans_MNIST","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tschechlovdev%2Fkmeans_MNIST","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tschechlovdev%2Fkmeans_MNIST/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tschechlovdev%2Fkmeans_MNIST/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tschechlovdev%2Fkmeans_MNIST/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tschechlovdev","download_url":"https://codeload.github.com/tschechlovdev/kmeans_MNIST/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tschechlovdev%2Fkmeans_MNIST/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32738798,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-07T02:14:30.463Z","status":"ssl_error","status_checked_at":"2026-05-07T02:14:29.405Z","response_time":62,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["clustering","image-dataset","python","scikit-learn"],"created_at":"2025-02-15T01:38:24.738Z","updated_at":"2026-05-07T13:01:56.843Z","avatar_url":"https://github.com/tschechlovdev.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Applying k-Means on the Image Dataset MNIST\n\nThis repository showcases how to apply k-Means on the image dataset MNIST.\nIn particular, how to load the data, apply k-Means, visualize the results, and how to evaluate it.\n\nYou can find the corresponding post on Medium [here](https://medium.com/@tschechd/applying-understanding-k-means-on-image-data-using-the-mnist-dataset-8101fcc650eb).\n\n## Installation\n\nThe notebook is written in Python 3.10. I suggest to install [Anaconda](https://docs.anaconda.com/).\nTo install the same environment you can simply run ``conda env create -f environment.yml``.\n\nAlternatively, you can lookup the dependencies in the environment.yml file and install them, e.g., using pip.\n\nThen just run ``jupyter-lab`` and open the ``kmeans_MNIST.ipynb`` notebook.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftschechlovdev%2Fkmeans_mnist","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftschechlovdev%2Fkmeans_mnist","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftschechlovdev%2Fkmeans_mnist/lists"}