{"id":16393845,"url":"https://github.com/avrabyt/technble-demo","last_synced_at":"2026-05-06T06:39:30.354Z","repository":{"id":110072332,"uuid":"532200500","full_name":"avrabyt/technble-demo","owner":"avrabyt","description":"Preditcs football player's playing position","archived":false,"fork":false,"pushed_at":"2022-09-03T21:44:01.000Z","size":14035,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-04T04:16:03.523Z","etag":null,"topics":["demo-app","football-data","k-nearest-neighbors-k-nn","machine-learning-algorithms","python","streamlit"],"latest_commit_sha":null,"homepage":"https://avrabyt-technble-demo-demo-4t709i.streamlitapp.com","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/avrabyt.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":"2022-09-03T08:25:38.000Z","updated_at":"2022-09-03T21:11:01.000Z","dependencies_parsed_at":"2023-04-03T16:50:03.991Z","dependency_job_id":null,"html_url":"https://github.com/avrabyt/technble-demo","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/avrabyt%2Ftechnble-demo","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/avrabyt%2Ftechnble-demo/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/avrabyt%2Ftechnble-demo/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/avrabyt%2Ftechnble-demo/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/avrabyt","download_url":"https://codeload.github.com/avrabyt/technble-demo/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240258790,"owners_count":19773058,"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":["demo-app","football-data","k-nearest-neighbors-k-nn","machine-learning-algorithms","python","streamlit"],"created_at":"2024-10-11T04:54:21.275Z","updated_at":"2026-05-06T06:39:25.325Z","avatar_url":"https://github.com/avrabyt.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Live Master Class - Demo app \n\nPreditcs player's playing position - Minimalistic app build on trained model with [k-Nearest Neighbors algorithm](https://www.ibm.com/topics/knn). \n\n```yaml\nCharlie Jackson:\n- K-Nearest Neighbors is a clustering algorithm used to classify new data based upon its 'closeness' to other laballed data points. \n- As it uses labeled data to make predictions on new data, it is a supervised learning technique. \n- The features for k-Nearest Neighbor algorithm must be continous rather than categorical.\n```\n\nFor example, clustering based on centroids position, figure below self-explains the idea behind, (*however, not from the current example tried here*)\n\n![demo](https://github.com/avrabyt/technble-demo/blob/main/Resources/demo.png)\n\u003e **Note**\n\n\u003e Try the app [here](https://avrabyt-technble-demo-demo-4t709i.streamlitapp.com/) [app is under development]\n\n------------------------\n### Resources\n1. https://charlieojackson.co.uk/python/predicting-football-positions.php?fbclid=IwAR34jqESq_86XzCuVtn7E9SgN4t3nQHhQMWscpjvrthagEG0fufHOCazFjs\n2. https://www.kaggle.com/code/bennyf/player-position-classification/notebook?fbclid=IwAR34d_eC313oW0rkNQL3jTb0F_Oozs7zGuVwCCWatZf-gGjsWtu4mlEltN8\n\n### Data \n- https://www.kaggle.com/datasets/stefanoleone992/fifa-22-complete-player-dataset?select=players_22.csv\n- https://www.kaggle.com/datasets/stefanoleone992/fifa-20-complete-player-dataset\n-----------------------------------------\n\u003e **Note**\n\u003e ### Schedule\n\n\u003e ![thumbnail](https://github.com/avrabyt/technble-demo/blob/main/Resources/live.jpeg)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Favrabyt%2Ftechnble-demo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Favrabyt%2Ftechnble-demo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Favrabyt%2Ftechnble-demo/lists"}