{"id":25221864,"url":"https://github.com/ruoheng-du/applied-machine-learning","last_synced_at":"2025-08-30T18:21:04.921Z","repository":{"id":276428142,"uuid":"865715873","full_name":"ruoheng-du/applied-machine-learning","owner":"ruoheng-du","description":"Applied Machine Learning | Fall 2024","archived":false,"fork":false,"pushed_at":"2025-02-08T06:17:36.000Z","size":3068,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-05T12:12:10.999Z","etag":null,"topics":["imbalanced-data","linear-models","natural-language-processing","neural-networks","svm-model","tree-based-models"],"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/ruoheng-du.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":"2024-10-01T02:17:49.000Z","updated_at":"2025-02-08T06:17:39.000Z","dependencies_parsed_at":"2025-02-08T07:20:22.137Z","dependency_job_id":"a676278a-5a35-44e7-8227-f440b2534241","html_url":"https://github.com/ruoheng-du/applied-machine-learning","commit_stats":null,"previous_names":["ruoheng-du/applied-machine-learning"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ruoheng-du/applied-machine-learning","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ruoheng-du%2Fapplied-machine-learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ruoheng-du%2Fapplied-machine-learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ruoheng-du%2Fapplied-machine-learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ruoheng-du%2Fapplied-machine-learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ruoheng-du","download_url":"https://codeload.github.com/ruoheng-du/applied-machine-learning/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ruoheng-du%2Fapplied-machine-learning/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272886929,"owners_count":25009923,"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","status":"online","status_checked_at":"2025-08-30T02:00:09.474Z","response_time":77,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["imbalanced-data","linear-models","natural-language-processing","neural-networks","svm-model","tree-based-models"],"created_at":"2025-02-10T22:53:25.173Z","updated_at":"2025-08-30T18:21:04.900Z","avatar_url":"https://github.com/ruoheng-du.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Applied Machine Learning | Fall 2024\nThis repository contains code implementations and analysis done in the Applied Machine Learning course during Fall 2024. The course focuses on practical applications of machine learning techniques, exploring various algorithms, tools, and approaches to solve real-world data-driven problems. The objective of the course is to understand machine learning algorithms to solve structured and unstructured data problems, and address challenges in model training, such as overfitting, underfitting, and class imbalance. The repository is organized into the following key notebooks:\n\n1. **Linear_Models_SVMs.ipynb**  \n   Implementation and analysis of linear models and Support Vector Machines (SVMs) for classification and regression tasks.\n\n\u003cimg width=\"700\" alt=\"notebook1\" src=\"https://github.com/ruoheng-du/applied-machine-learning/raw/main/assets/notebook1.png\"\u003e\n\n2. **Tree-based_Ensemble_Models.ipynb**  \n   Application of tree-based ensemble methods like Random Forests and Gradient Boosting to enhance predictive performance and interpretability.\n\n\u003cimg width=\"700\" alt=\"notebook2\" src=\"https://github.com/ruoheng-du/applied-machine-learning/raw/main/assets/notebook2.png\"\u003e\n\n3. **Imbalanced_Dataset.ipynb**  \n   Techniques and strategies to handle imbalanced datasets, including resampling methods and evaluation metrics tailored for imbalanced data.\n\n\u003cimg width=\"500\" alt=\"notebook3\" src=\"https://github.com/ruoheng-du/applied-machine-learning/raw/main/assets/notebook3.png\"\u003e\n\n4. **Natural_Language_Processing.ipynb**  \n   Exploration of NLP techniques, including text preprocessing, tokenization, and machine learning-based language models.\n\n\u003cimg width=\"400\" alt=\"notebook4-1\" src=\"https://github.com/ruoheng-du/applied-machine-learning/raw/main/assets/notebook4-1.png\"\u003e\u003cimg width=\"400\" alt=\"notebook4-2\" src=\"https://github.com/ruoheng-du/applied-machine-learning/raw/main/assets/notebook4-2.png\"\u003e\n\n5. **Neural_Networks.ipynb**  \n   Development and training of neural network models for complex prediction tasks, including hyperparameter tuning and performance evaluation.\n\n\u003cimg width=\"500\" alt=\"notebook5\" src=\"https://github.com/ruoheng-du/applied-machine-learning/raw/main/assets/notebook5.png\"\u003e\n\nPlease feel free to email me at ruoheng.du@columbia.edu for any more information.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fruoheng-du%2Fapplied-machine-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fruoheng-du%2Fapplied-machine-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fruoheng-du%2Fapplied-machine-learning/lists"}