{"id":23396020,"url":"https://github.com/waleedgeorgy/ml_sklearn","last_synced_at":"2026-04-26T12:31:34.162Z","repository":{"id":266502401,"uuid":"898529476","full_name":"waleedGeorgy/ml_sklearn","owner":"waleedGeorgy","description":"Implementation of various machine learning algorithms for regression and classification \u0026 feature engineering.","archived":false,"fork":false,"pushed_at":"2024-12-04T15:40:52.000Z","size":12666,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-08T17:19:49.673Z","etag":null,"topics":["data-visualization","jupyter-notebook","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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/waleedGeorgy.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":"2024-12-04T15:00:36.000Z","updated_at":"2024-12-29T13:05:58.000Z","dependencies_parsed_at":null,"dependency_job_id":"f9655602-5251-49ea-92bd-cd248f58212e","html_url":"https://github.com/waleedGeorgy/ml_sklearn","commit_stats":null,"previous_names":["waleedgeorgy/ml_sklearn"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/waleedGeorgy/ml_sklearn","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waleedGeorgy%2Fml_sklearn","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waleedGeorgy%2Fml_sklearn/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waleedGeorgy%2Fml_sklearn/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waleedGeorgy%2Fml_sklearn/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/waleedGeorgy","download_url":"https://codeload.github.com/waleedGeorgy/ml_sklearn/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/waleedGeorgy%2Fml_sklearn/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32297893,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-26T09:34:17.070Z","status":"ssl_error","status_checked_at":"2026-04-26T09:34:00.993Z","response_time":129,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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-visualization","jupyter-notebook","machine-learning","python"],"created_at":"2024-12-22T07:20:00.037Z","updated_at":"2026-04-26T12:31:34.146Z","avatar_url":"https://github.com/waleedGeorgy.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Supervised Machine Learning With Scikit-Learn\nImplementation of various machine learning algorithms for supervised regression and classification. Namely:\n- Linear Regression.\n- Multinomial Regression.\n- Logistic Regression.\n- K-Nearest Neightbour Clustering.\n- Support Vector Machines (SVMs).\n- Decision Trees.\n- Random Forests.\n- AdaBoosting.\n- Gradient Boosting.\n- Naive Bayes.\u003cbr /\u003e\nAll this was done along with feature engineering and datasets cleaning and exploration, and using different regularization and cross-validation.\u003cbr /\u003e\nData exploration and visualization was done using various different types of matplotlib plots and NumPy and Pandas functions.\n\n## Unsupervised Machine Learning With Scikit-Learn\nSimilar to the above, but using algorithms like:\n- K-Means Clustering.\n- Hierarchical Clustering.\n- DBSCAN.\n- Principal Component Analysis (PCA).\u003cbr /\u003e\nIn the unsupervised section, model deployment and persistence was also implemented.\n\nBoth notebooks contain models that are ready to train and deploy.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwaleedgeorgy%2Fml_sklearn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwaleedgeorgy%2Fml_sklearn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwaleedgeorgy%2Fml_sklearn/lists"}