{"id":13717723,"url":"https://github.com/hpcgarage/accelerated_dl_pytorch","last_synced_at":"2025-10-29T02:56:04.564Z","repository":{"id":80678276,"uuid":"127490270","full_name":"hpcgarage/accelerated_dl_pytorch","owner":"hpcgarage","description":"Accelerated Deep Learning with PyTorch at Jupyter Day Atlanta II","archived":false,"fork":false,"pushed_at":"2018-04-05T20:02:12.000Z","size":1030,"stargazers_count":127,"open_issues_count":0,"forks_count":29,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-05-07T07:40:08.225Z","etag":null,"topics":[],"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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/hpcgarage.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}},"created_at":"2018-03-31T02:05:07.000Z","updated_at":"2024-04-09T08:17:39.000Z","dependencies_parsed_at":null,"dependency_job_id":"a3f83a9c-433d-4073-8e52-61dc2adf84bf","html_url":"https://github.com/hpcgarage/accelerated_dl_pytorch","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/hpcgarage/accelerated_dl_pytorch","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hpcgarage%2Faccelerated_dl_pytorch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hpcgarage%2Faccelerated_dl_pytorch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hpcgarage%2Faccelerated_dl_pytorch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hpcgarage%2Faccelerated_dl_pytorch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hpcgarage","download_url":"https://codeload.github.com/hpcgarage/accelerated_dl_pytorch/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hpcgarage%2Faccelerated_dl_pytorch/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":281549786,"owners_count":26520515,"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","status":"online","status_checked_at":"2025-10-29T02:00:06.901Z","response_time":59,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":[],"created_at":"2024-08-03T00:01:26.080Z","updated_at":"2025-10-29T02:56:04.552Z","avatar_url":"https://github.com/hpcgarage.png","language":"Jupyter Notebook","funding_links":[],"categories":["Tutorials \u0026 books \u0026 examples｜教程 \u0026 书籍 \u0026 示例","Tutorials, books, \u0026 examples"],"sub_categories":["Other libraries｜其他库:","Other libraries:"],"readme":"# accelerated_dl_pytorch\nThis is the repository for **Accelerated Deep Learning with Pytotch** tutorial and [**Jupyter Day Atlanta 2018**](https://github.com/atl-jugheads/jupyter-day-atlanta-ii) talk slides. It features full tutorial notebook, Jupyter Notebook Slides html file, and a demo with surface finish quality inspection.\n\n## Knowledge Prerequisites\nThis tutorial assumes familiarity with Python and Numpy.\n\n## Tutorial Prerequisites\nPython3 is required to run this tutorial. You also will need some libraries from SciPy package (NumPy, Matplotlib, Pandas), Jupyter Notebook support, Seaborn for plotting, and Pytorch 0.3.0 or newer.\n\nThe simpliest way to maintain Python with all these libraries as well as many others is to install [Anaconda](https://www.anaconda.com/download). You can Find Pytorch installation instructions on the [Pytorch page](http://pytorch.org).\n\nCUDA availability is not strictly required, but highly desirable. Life is short -- use a GPU!\n\n## How to Use\nOur tutorial git has two submodules - for surface dataset, and for pretrained model for surface finish quality inspection. To download the tutorial, use \n\n```\ngit clone --recurse-submodules git@github.com:hpcgarage/accelerated_dl_pytorch.git\n```\n\nIf you didn't clone repository with its submodules, you can always clone submodules with this command:\n\n```\ngit submodule update --init --recursive\n```\n\nTo run the Jupyter Notebook Slides as at Jupyter Day Atlanta 2018 talk, you can use following command:\n\n```\njupyter nbconvert tutorial_presentation.ipynb --to slides --post serve\n```\n\n## Table of Contents\n1. Essential PyTorch Background\n2. PyTorch for Data Analytics\n3. LeNet Convolutional Neural Network (CNN) in PyTorch\n4. Application to a Manufacturing Problem\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhpcgarage%2Faccelerated_dl_pytorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhpcgarage%2Faccelerated_dl_pytorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhpcgarage%2Faccelerated_dl_pytorch/lists"}