{"id":21421394,"url":"https://github.com/percival33/machine-learning-engineering","last_synced_at":"2025-07-14T07:32:43.159Z","repository":{"id":229383950,"uuid":"720764152","full_name":"Percival33/Machine-Learning-Engineering","owner":"Percival33","description":"Uni project about enhancing fictional music streaming service, by developing machine learning models to generate popular playlists","archived":true,"fork":false,"pushed_at":"2024-03-23T23:48:19.000Z","size":2458,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-16T20:13:54.484Z","etag":null,"topics":["data-analysis","data-science","machine-learning","python"],"latest_commit_sha":null,"homepage":"","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/Percival33.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}},"created_at":"2023-11-19T14:32:23.000Z","updated_at":"2024-07-25T21:04:42.000Z","dependencies_parsed_at":"2024-03-24T00:38:07.216Z","dependency_job_id":null,"html_url":"https://github.com/Percival33/Machine-Learning-Engineering","commit_stats":null,"previous_names":["percival33/machine-learning-engineering"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Percival33/Machine-Learning-Engineering","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FMachine-Learning-Engineering","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FMachine-Learning-Engineering/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FMachine-Learning-Engineering/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FMachine-Learning-Engineering/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Percival33","download_url":"https://codeload.github.com/Percival33/Machine-Learning-Engineering/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Percival33%2FMachine-Learning-Engineering/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265255275,"owners_count":23735223,"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":["data-analysis","data-science","machine-learning","python"],"created_at":"2024-11-22T20:33:57.969Z","updated_at":"2025-07-14T07:32:42.852Z","avatar_url":"https://github.com/Percival33.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning Engineering\n\n## Team\n\n- Miłosz Mizak\n- Marcin Jarczewski\n\n## Project Overview\n\nThis project is a part of the Machine Learning Engineering at Warsaw University of Technology course aimed at developing a practical solution for \"Pozytywka,\" an online music streaming service. As analysts, we step into the role of tackling a vaguely described task, requiring us to specify details for implementation. The challenge involves understanding the problem, analyzing data, and sometimes negotiating with management (tutor) to ensure the models are production-ready and future-proof for subsequent versions.\n\n### Data Collection\n\n\"Pozytywka\" collects data crucial for this project, including:\n\n- A list of available artists and music tracks\n- A user database\n- User session history\n- Technical information regarding the caching level of individual tracks\n\n## Task\n\nExtend the \"Pozytywka\" service by generating popular playlists – sets of matching songs tailored to capture the interest of a broad audience. This initiative aims to enhance user engagement by offering compilations based on the most popular music genres, updated weekly with 10 to 20 songs each.\n\n## Project Phases\n\n### Stage 1\n\n- Define the business problem, modeling tasks, assumptions, and success criteria.\n- Analyze the provided data to assess sufficiency for task realization, identifying any gaps or requirements for additional data.\n\nReport available [here](https://github.com/Percival33/Machine-Learning-Engineering/blob/main/reports/JarczewskiMizak_05wariant02_etap1.ipynb) (in Polish).\n\n### Stage 2\n\n1. **Model Development:**\n   - Develop a baseline model (the simplest possible for the given task).\n   - Develop an advanced target model.\n   - Report detailing the model building process and comparing results.\n2. **Application Implementation:**\n   - Implement an application (as a microservice) that:\n     - Serves predictions using the developed model.\n     - Conducts an A/B experiment comparing both models and collects data for later quality assessment.\n3. **Demonstration Materials:**\n   - Provide materials showing the implementation is functional.\n\nReport available [here](https://github.com/Percival33/Machine-Learning-Engineering/blob/main/reports/JarczewskiMizak_05_wariant02_etap2.ipynb) (in Polish).\n\n\u003cp\u003e\u003csmall\u003eProject based on the \u003ca target=\"_blank\" href=\"https://drivendata.github.io/cookiecutter-data-science/\"\u003ecookiecutter data science project template\u003c/a\u003e. #cookiecutterdatascience\u003c/small\u003e\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpercival33%2Fmachine-learning-engineering","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpercival33%2Fmachine-learning-engineering","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpercival33%2Fmachine-learning-engineering/lists"}