{"id":13477358,"url":"https://github.com/argonne-lcf/ATPESC_MachineLearning","last_synced_at":"2025-03-27T05:31:34.162Z","repository":{"id":56706816,"uuid":"200883914","full_name":"argonne-lcf/ATPESC_MachineLearning","owner":"argonne-lcf","description":"Lecture and hands-on material for Track 8- Machine Learning of  Argonne Training Program on Extreme-Scale Computing","archived":false,"fork":false,"pushed_at":"2024-08-09T18:47:50.000Z","size":150286,"stargazers_count":37,"open_issues_count":0,"forks_count":27,"subscribers_count":15,"default_branch":"master","last_synced_at":"2025-03-20T16:05:29.356Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://extremecomputingtraining.anl.gov/","language":"LLVM","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/argonne-lcf.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":"2019-08-06T16:03:32.000Z","updated_at":"2025-03-07T17:20:03.000Z","dependencies_parsed_at":"2024-08-09T16:28:23.027Z","dependency_job_id":"c2dadfe6-c92d-4ee2-a142-d893b91c691c","html_url":"https://github.com/argonne-lcf/ATPESC_MachineLearning","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FATPESC_MachineLearning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FATPESC_MachineLearning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FATPESC_MachineLearning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/argonne-lcf%2FATPESC_MachineLearning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/argonne-lcf","download_url":"https://codeload.github.com/argonne-lcf/ATPESC_MachineLearning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245791523,"owners_count":20672665,"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":[],"created_at":"2024-07-31T16:01:41.629Z","updated_at":"2025-03-27T05:31:29.145Z","avatar_url":"https://github.com/argonne-lcf.png","language":"LLVM","readme":"# [ATPESC 2024](https://extremecomputingtraining.anl.gov/agenda-2024/)\n\nAt the beginning of the day, we will temporarily split into two groups. Attendees can choose between \"Introduction to deep learning\" (01_deepLearning) and \"Building data pipelines\" (02_dataPipelines).  \n\nThe \"Introduction to deep learning\" session will rely on Jupyter Notebooks which are targeted for running on [Google's Colaboratory Platform](https://colab.research.google.com) or [ALCF JupyterHub](https://www.alcf.anl.gov/support-center/theta/jupyter-hub). The Colab platform gives the user a virtual machine in which to run Python codes including machine learning codes. The VM comes with a preinstalled environment that includes most of what is needed for these tutorials.\n\nThe other sessions involve Python scripts executed on the [Polaris](https://docs.alcf.anl.gov/polaris/getting-started/) and [AI Testbed](https://www.alcf.anl.gov/alcf-ai-testbed) platforms at ALCF. \n\n## Using Google Colab\nGoogle Colab involves running Jupyter notebooks, which you have experience with from earlier in the week. \n\nDo the following before you come to the tutorial:\n*  You need a Google Account to use Colaboratory\n*  Go to [Google's Colaboratory Platform](https://colab.research.google.com) \n*  You should see this page\n![start_page](README_imgs/colab_start_page.png)\n*  Now you can open the `File` menu at the top left and select `Open Notebook` which will open a dialogue box.\n*  Select the `GitHub` tab in the dialogue box.\n*  From here you can enter the url for the github repo: `https://github.com/argonne-lcf/ATPESC_MachineLearning` and hit `\u003center\u003e`.\n![open_github](README_imgs/colab_open_github.png)\n*  This will show you a list of the Notebooks available in the repo. When you select a notebook from this list it will create a copy for you in your Colaboratory account (all `*.ipynb` files in the Colaboratory account will be stored in your Google Drive).\n* To use a GPU in the notbook select `Runtime` -\u003e `Change Runtime Type` and select an accelerator.\n","funding_links":[],"categories":["LLVM"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargonne-lcf%2FATPESC_MachineLearning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fargonne-lcf%2FATPESC_MachineLearning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargonne-lcf%2FATPESC_MachineLearning/lists"}