{"id":20811427,"url":"https://github.com/cyberfantics/data-mining","last_synced_at":"2025-03-12T04:43:43.462Z","repository":{"id":262378948,"uuid":"887051572","full_name":"cyberfantics/data-mining","owner":"cyberfantics","description":null,"archived":false,"fork":false,"pushed_at":"2025-01-26T15:53:55.000Z","size":469,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-26T16:22:46.883Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/cyberfantics.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":"2024-11-12T04:42:08.000Z","updated_at":"2025-01-26T15:53:58.000Z","dependencies_parsed_at":"2024-11-12T05:28:13.537Z","dependency_job_id":"cce6f9df-c75d-4a5c-9761-9d42606a9f37","html_url":"https://github.com/cyberfantics/data-mining","commit_stats":null,"previous_names":["cyberfantics/data-mining"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cyberfantics%2Fdata-mining","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cyberfantics%2Fdata-mining/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cyberfantics%2Fdata-mining/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cyberfantics%2Fdata-mining/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cyberfantics","download_url":"https://codeload.github.com/cyberfantics/data-mining/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243158972,"owners_count":20245669,"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":[],"created_at":"2024-11-17T20:41:22.623Z","updated_at":"2025-03-12T04:43:43.440Z","avatar_url":"https://github.com/cyberfantics.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Mining Course Repository\n\nWelcome to the **Data Mining Course Repository** for BS 7. This repository contains all resources, code, and assignments related to the Data Mining course, aimed at building a strong foundation in data analysis and knowledge discovery.\n\n## Course Overview\nData mining involves extracting valuable insights from large datasets, uncovering patterns, and supporting decision-making processes. This course covers fundamental techniques, algorithms, and tools used in data mining, including preprocessing, classification, clustering, association analysis, and more.\n\n## Repository Structure\nThe repository is organized as follows:\n\n- **Lecture Notes**: Contains lecture slides, notes, and references.\n- **Assignments**: Includes all assignments given during the course, along with solutions.\n- **Projects**: Holds project files and code relevant to various data mining tasks.\n- **Datasets**: Provides datasets used for exercises, assignments, and projects.\n\n## Course Topics\nThe following topics are covered in this course:\n\n1. **Data Preprocessing**: Cleaning and preparing data for analysis.\n2. **Classification**: Algorithms for categorizing data, including decision trees, Naive Bayes, and k-NN.\n3. **Clustering**: Techniques for grouping data, such as k-means and hierarchical clustering.\n4. **Association Rule Mining**: Discovering relationships between variables in large datasets.\n5. **Dimensionality Reduction**: Reducing data complexity for visualization and processing.\n6. **Evaluation Metrics**: Techniques to assess model performance.\n\n## Getting Started\nTo get started, clone this repository:\n```\ngit clone https://github.com/cyberfantics/data-mining.git\n```\n\n## Prerequisites\n- Python 3.x\n- **Libraries:** numpy, pandas, matplotlib, scikit-learn\n\n## Install required libraries with:\n```\npip install -r requirements.txt\n```\n\n### How to Use This Repository\n- Read through lecture notes to understand the concepts.\n- Complete the assignments by following the provided instructions.\n- Experiment with datasets and try out different data mining techniques.\n\n### Contributing\n- If you have suggestions or improvements, feel free to submit a pull request. Contributions are welcome!\n- \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcyberfantics%2Fdata-mining","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcyberfantics%2Fdata-mining","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcyberfantics%2Fdata-mining/lists"}