{"id":16782235,"url":"https://github.com/abhinav-26/accuracy-achiever","last_synced_at":"2025-07-14T10:31:20.143Z","repository":{"id":56560112,"uuid":"267856451","full_name":"Abhinav-26/Accuracy-Achiever","owner":"Abhinav-26","description":"Accuracy Achiever is an Automation Project of MLOps build by Integrating Machine Learning and DevOps.","archived":false,"fork":false,"pushed_at":"2021-04-20T10:58:58.000Z","size":42,"stargazers_count":3,"open_issues_count":0,"forks_count":7,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-04-08T06:19:39.539Z","etag":null,"topics":["accuracy-achiever","devops","hactoberfest","hactoberfest2020","machine-learning","machine-learning-with-devops","mlops"],"latest_commit_sha":null,"homepage":"","language":"Python","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/Abhinav-26.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}},"created_at":"2020-05-29T12:48:40.000Z","updated_at":"2022-11-26T00:50:44.000Z","dependencies_parsed_at":"2022-08-15T21:00:26.611Z","dependency_job_id":null,"html_url":"https://github.com/Abhinav-26/Accuracy-Achiever","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Abhinav-26/Accuracy-Achiever","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhinav-26%2FAccuracy-Achiever","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhinav-26%2FAccuracy-Achiever/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhinav-26%2FAccuracy-Achiever/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhinav-26%2FAccuracy-Achiever/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Abhinav-26","download_url":"https://codeload.github.com/Abhinav-26/Accuracy-Achiever/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Abhinav-26%2FAccuracy-Achiever/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265280523,"owners_count":23739850,"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":["accuracy-achiever","devops","hactoberfest","hactoberfest2020","machine-learning","machine-learning-with-devops","mlops"],"created_at":"2024-10-13T07:44:44.821Z","updated_at":"2025-07-14T10:31:19.771Z","avatar_url":"https://github.com/Abhinav-26.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Accuracy-Achiever : MLOps\nIn this repository I have uploaded python code which I have used for my setup of accuracy achiever. In this setup I have tried to create an environment such that It will automatically train my model and it will train utill it gets the desired accuarcy. For this setup I used DevOps tools. I have integrated DeepLearning model with DevOps tools like docker and jenkins.\u003cbr\u003e\n\nIn this Project I have created a docker image with deepLearning libraries like tensorflow2.0, scikit-learn, keras, etc and uploaded the image in my \u003ca href=\"https://hub.docker.com/u/alex43\"\u003eDockerHub Profile\u003c/a\u003e. I have created two images named \u003cb\u003ealex43/ubuntu-tensorflow2.0\u003c/b\u003e and \u003cb\u003ealex43/ubuntu-deeplearning-env\u003c/b\u003e. For this Project I have used the \u003ca href=\"https://hub.docker.com/r/alex43/ubuntu-deeplearning-env\"\u003edeeplearning-env image\u003c/a\u003e.\u003cbr\u003e\n\nTo Download the image in your system write the command given below :\u003cbr\u003e\n\u003ccode\u003edocker pull alex43/ubuntu-deeplearning-env\u003c/code\u003e\n\nFor the demo of this project \u003ca href=\"https://www.linkedin.com/posts/abhinavdubey26_mlops-machinelearning-deeplearning-activity-6672503330020970496-cBWO\"\u003eclick here.\u003c/a\u003e\u003cbr\u003e\n\n\nThe Project has also being recognised by Jenkins Community and you can read the complete article from \u003ca href=\"https://jenkinsistheway.io/user-story/to-achieve-accuracy/\"\u003ehere.\u003c/a\u003e Also I recieved swags from \u003ca href=\"https://www.linkedin.com/feed/update/urn:li:activity:6755097801086038016/\"\u003eJenkins Is The Way\u003c/a\u003e for this project.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhinav-26%2Faccuracy-achiever","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhinav-26%2Faccuracy-achiever","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhinav-26%2Faccuracy-achiever/lists"}