{"id":28575161,"url":"https://github.com/ferdos-coder/machine-learning-linear-models","last_synced_at":"2025-10-24T08:22:25.841Z","repository":{"id":289439844,"uuid":"967533581","full_name":"ferdos-coder/machine-learning-linear-models","owner":"ferdos-coder","description":null,"archived":false,"fork":false,"pushed_at":"2025-04-23T08:54:42.000Z","size":372,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-06-28T10:42:39.011Z","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/ferdos-coder.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,"zenodo":null}},"created_at":"2025-04-16T15:47:01.000Z","updated_at":"2025-04-23T08:54:46.000Z","dependencies_parsed_at":"2025-04-23T09:49:48.846Z","dependency_job_id":null,"html_url":"https://github.com/ferdos-coder/machine-learning-linear-models","commit_stats":null,"previous_names":["ferdos-coder/machine-learning-linear-models"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ferdos-coder/machine-learning-linear-models","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ferdos-coder%2Fmachine-learning-linear-models","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ferdos-coder%2Fmachine-learning-linear-models/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ferdos-coder%2Fmachine-learning-linear-models/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ferdos-coder%2Fmachine-learning-linear-models/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ferdos-coder","download_url":"https://codeload.github.com/ferdos-coder/machine-learning-linear-models/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ferdos-coder%2Fmachine-learning-linear-models/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270639078,"owners_count":24620655,"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":"2025-08-15T02:00:12.559Z","response_time":110,"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":[],"created_at":"2025-06-10T22:41:07.987Z","updated_at":"2025-10-24T08:22:25.756Z","avatar_url":"https://github.com/ferdos-coder.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning Linear Models\n\nThis repository contains practical examples and resources for building and training linear models in machine learning using Python. It focuses on applying linear regression techniques to real-world datasets, demonstrating the full workflow from data preparation to model evaluation.\n\n---\n\n## Table of Contents\n\n- [Project Overview](#project-overview)  \n- [Dataset](#dataset)  \n- [Contents](#contents)\n\n---\n\n## Project Overview\n\nThis project aims to provide hands-on experience with linear models in machine learning, particularly linear regression. Using Python and popular libraries such as scikit-learn and pandas, it covers:\n\n- Loading and exploring datasets  \n- Preparing data for modeling  \n- Training linear regression models  \n- Saving and loading trained models  \n- Evaluating model performance  \n- Practical examples with real datasets  \n\nThe project is ideal for beginners and intermediate learners who want to understand how linear models work and how to implement them effectively.\n\n---\n\n## Dataset\n\nThe repository includes the `Advertising.csv` dataset, which contains advertising budgets across different media channels and corresponding sales figures. This dataset is commonly used for regression tasks and model training demonstrations.\n\n---\n\n## Contents\n\n- `Advertising.csv` — Dataset file  \n- `adv.ipynb` — Jupyter Notebook with step-by-step implementation of linear regression on the advertising dataset  \n- `machinelearningfitmodel.ipynb` — Notebook demonstrating fitting and saving a linear regression model  \n- `final_sales_mode.joblib` — A saved model file for reuse  \n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fferdos-coder%2Fmachine-learning-linear-models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fferdos-coder%2Fmachine-learning-linear-models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fferdos-coder%2Fmachine-learning-linear-models/lists"}