{"id":18096641,"url":"https://github.com/andreaschandra/ax-playground","last_synced_at":"2025-10-17T15:56:33.577Z","repository":{"id":115162907,"uuid":"332661995","full_name":"andreaschandra/ax-playground","owner":"andreaschandra","description":"Adaptive Experimentation Platform - Playground","archived":false,"fork":false,"pushed_at":"2021-02-01T08:09:44.000Z","size":4003,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-02-12T09:49:51.101Z","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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/andreaschandra.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-01-25T07:16:48.000Z","updated_at":"2023-08-12T17:45:14.000Z","dependencies_parsed_at":"2023-04-17T20:18:28.697Z","dependency_job_id":null,"html_url":"https://github.com/andreaschandra/ax-playground","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/andreaschandra%2Fax-playground","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andreaschandra%2Fax-playground/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andreaschandra%2Fax-playground/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andreaschandra%2Fax-playground/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/andreaschandra","download_url":"https://codeload.github.com/andreaschandra/ax-playground/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247430008,"owners_count":20937785,"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":"2024-10-31T19:14:59.893Z","updated_at":"2025-09-17T20:04:12.718Z","avatar_url":"https://github.com/andreaschandra.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ax-playground\nAdaptive Experimentation Platform - Playground\n\nAx is a platform for optimizing any kind of experiment, including machine learning experiments, A/B tests, and simulations. Ax can optimize discrete configurations (e.g., variants of an A/B test) using multi-armed bandit optimization, and continuous (e.g., integer or floating point)-valued configurations using Bayesian optimization. This makes it suitable for a wide range of applications.\n\nAx has been successfully applied to a variety of product, infrastructure, ML, and research applications at Facebook.\n\n_https://ax.dev/docs/why-ax.html_\n\n## Installation\nThe library strongly encourage you to install via pip and conda for OSX\n\n```\nconda install pytorch torchvision -c pytorch  # OSX only (details below)\npip3 install ax-platform\n```\n\n## Highlights\n\nTutorial References:\n- https://ax.dev/tutorials/tune_cnn.html\n- https://towardsdatascience.com/quick-tutorial-using-bayesian-optimization-to-tune-your-hyperparameters-in-pytorch-e9f74fc133c2\n- https://www.justintodata.com/hyperparameter-tuning-with-python-keras-guide/\n\nKey points:\n- Well documented (better) than BoTorch\n- There are 3 types of usage in order to tune your parameters: Loop API, Service API, Developer API.\n- There are 2 Algorithms: Bayesian and Bandit Optimization\n- built-in feature that enables saving results to a JSON file or a MySQL database.\n- able to create such as complext dependent parameter constraints.\n- Integrate visualization using plotly and stunning visualization.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandreaschandra%2Fax-playground","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandreaschandra%2Fax-playground","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandreaschandra%2Fax-playground/lists"}