{"id":20057309,"url":"https://github.com/natbusa/deepnumbers","last_synced_at":"2025-05-05T14:31:07.058Z","repository":{"id":147332145,"uuid":"77740451","full_name":"natbusa/deepnumbers","owner":"natbusa","description":"A set of educational deep learning demos applied to the MNIST dataset","archived":false,"fork":false,"pushed_at":"2017-04-18T13:08:20.000Z","size":3558,"stargazers_count":9,"open_issues_count":0,"forks_count":11,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-26T08:07:34.881Z","etag":null,"topics":["deep-learning-tutorial","deep-neural-networks","machine-learning"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/natbusa.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2016-12-31T13:01:28.000Z","updated_at":"2023-05-30T21:34:12.000Z","dependencies_parsed_at":"2023-05-11T05:15:41.963Z","dependency_job_id":null,"html_url":"https://github.com/natbusa/deepnumbers","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natbusa%2Fdeepnumbers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natbusa%2Fdeepnumbers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natbusa%2Fdeepnumbers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/natbusa%2Fdeepnumbers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/natbusa","download_url":"https://codeload.github.com/natbusa/deepnumbers/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252514880,"owners_count":21760452,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["deep-learning-tutorial","deep-neural-networks","machine-learning"],"created_at":"2024-11-13T12:58:24.941Z","updated_at":"2025-05-05T14:31:06.725Z","avatar_url":"https://github.com/natbusa.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# deepnumbers\nA set of educational deep learning demos applied to the MNIST dataset\n\n## Slides\n\nYou can find a presentation about this work at:  \nhttps://www.slideshare.net/natalinobusa/7-steps-for-highly-effective-deep-neural-networks\n\nHires pdf available here:\nhttps://drive.google.com/file/d/0BwNrPuGaMi8PbVhUYUVKWUhGRjQ\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/cover.png?raw\" alt=\"cover\"/\u003e\n\u003c/p\u003e\n\n## Brighttalk\nI do have a webinar on this one, thanks to the folks at Brighttalk.  \nCheck https://www.brighttalk.com/webcast/8251/252545\n\n## Youtube\nI thinking of taking screen captures of this project and posting it on youtube. So far my attempts have not been super successful (kudos to those pro youtubers out there - it's *definitely* not as easy as it looks).\n\n## Regression\n\n## SLP\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/slp.png?raw\" alt=\"slp mnist\"/\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/biology.png?raw\" alt=\"ann biology\"/\u003e\n\u003c/p\u003e\n\n## MLP\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/supervised.png?raw\" alt=\"supervised ann\"/\u003e\n\u003c/p\u003e\n\n## Convolutional\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/convblocks.png?raw\" alt=\"conv elements\"/\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/convnet.png?raw\" alt=\"convnet\"/\u003e\n\u003c/p\u003e\n\n## Batch Normalization\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/batchnorm.png?raw\" alt=\"batch normalization\"/\u003e\n\u003c/p\u003e\n\n## Inception\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/inception.png?raw\" alt=\"inception\"/\u003e\n\u003c/p\u003e\n\n## Residual\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/resnet.png?raw\" alt=\"residual networks\"/\u003e\n\u003c/p\u003e\n\n## LSTM on images\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/natbusa/deepnumbers/blob/master/images/lstm.png?raw\" alt=\"lstm on images\"/\u003e\n\u003c/p\u003e\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatbusa%2Fdeepnumbers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnatbusa%2Fdeepnumbers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatbusa%2Fdeepnumbers/lists"}