{"id":24605977,"url":"https://github.com/udacity-machinelearning-internship/polynomial-regression","last_synced_at":"2025-03-18T10:41:12.971Z","repository":{"id":239821987,"uuid":"800689315","full_name":"Udacity-MachineLearning-Internship/Polynomial-Regression","owner":"Udacity-MachineLearning-Internship","description":"Implementing polynomial regression using sckit-learn ","archived":false,"fork":false,"pushed_at":"2024-05-17T03:46:45.000Z","size":33,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-21T08:24:10.229Z","etag":null,"topics":["machine-learning","polynomial-regression","sckiit-learn"],"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/Udacity-MachineLearning-Internship.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":"2024-05-14T20:05:43.000Z","updated_at":"2024-12-17T20:43:48.000Z","dependencies_parsed_at":"2024-05-15T16:29:40.590Z","dependency_job_id":"ff485af6-1d3c-4add-b8ec-2563a1248bab","html_url":"https://github.com/Udacity-MachineLearning-Internship/Polynomial-Regression","commit_stats":null,"previous_names":["barasedih11/polynomial-regression","udacity-machinelearning-internship/polynomial-regression"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPolynomial-Regression","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPolynomial-Regression/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPolynomial-Regression/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPolynomial-Regression/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Udacity-MachineLearning-Internship","download_url":"https://codeload.github.com/Udacity-MachineLearning-Internship/Polynomial-Regression/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244206646,"owners_count":20416086,"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":["machine-learning","polynomial-regression","sckiit-learn"],"created_at":"2025-01-24T16:49:59.997Z","updated_at":"2025-03-18T10:41:12.945Z","avatar_url":"https://github.com/Udacity-MachineLearning-Internship.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv style=\"display:flex; justify-content: center; align-items: center ; height\" 100vh\" align=center\u003e\n\n![Polynomial_Regression](https://github.com/BaraSedih11/Polynomial-Regression/assets/98843912/62061da3-fb5f-4f90-9c35-d1ac2befa7ca)\n\n   ![GitHub repo size](https://img.shields.io/github/repo-size/BaraSedih11/Polynomial-Regression) ![GitHub repo file count (file type)](https://img.shields.io/github/directory-file-count/BaraSedih11/Polynomial-Regression) [![Python Version](https://img.shields.io/badge/python-3.8-blue)](https://www.python.org/downloads/release/python-380/)\n[![Pip Version](https://img.shields.io/badge/pip-21.0-orange)](https://pypi.org/project/pip/21.0/)\n ![GitHub last commit (branch)](https://img.shields.io/github/last-commit/BaraSedih11/Polynomial-Regression/main)\n[![Version](https://img.shields.io/badge/version-v1.0.0-blue)](https://github.com/BaraSedih11/Polynomial-Regression/releases/tag/v1.0.0)\n[![Contributors](https://img.shields.io/github/contributors/BaraSedih11/Polynomial-Regression)](https://github.com/BaraSedih11/Polynomial-Regression/graphs/contributors)\n![GitHub pull requests](https://img.shields.io/github/issues-pr-raw/BaraSedih11/Polynomial-Regression)\n\u003c!-- ![GitHub issues](https://img.shields.io/github/issues-raw/BaraSedih11/Bookstore)  --\u003e\n\u003c/div\u003e\nThis repository contains an implementation of polynomial regression using Python.\n\n## Overview\n\nPolynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial. It is used when the relationship between the variables is non-linear.\n\nIn this repository, we demonstrate how to perform polynomial regression using Python. We utilize libraries such as NumPy, pandas, scikit-learn, and matplotlib to implement and visualize the regression model. Additionally, we provide a simple example along with explanations to help you understand how to apply polynomial regression to your own datasets.\n\n## Contents\n\n- `polynomial_regression.ipynb`: Jupyter Notebook containing the implementation of polynomial regression using Python.\n- `data.csv`: Sample dataset used in the notebook for demonstration purposes.\n- `README.md`: This file providing an overview of the repository.\n\n## Requirements\n\nTo run the code in the Jupyter Notebook, you need to have Python installed on your system along with the following libraries:\n\n- NumPy\n- pandas\n- scikit-learn\n- matplotlib\n\nYou can install these libraries using pip:\n\n```bash\npip install numpy pandas scikit-learn matplotlib\n```\n\n\n## Usage\n\n1. Clone this repository to your local machine:\n\n```bash\ngit clone https://github.com/BaraSedih11/Polynomial-Regression.git\n```\n\n2. Navigate to the repository directory:\n\n```bash\ncd Polynomial-Regression\n```\n\n3. Open and run the Jupyter Notebook `polynomial_regression.ipynb` using Jupyter Notebook or JupyterLab.\n\n4. Follow along with the code and comments in the notebook to understand how polynomial regression is implemented using Python.\n\n## Acknowledgements\n\n- [scikit-learn](https://scikit-learn.org/): The scikit-learn library for machine learning in Python.\n- [NumPy](https://numpy.org/): The NumPy library for numerical computing in Python.\n- [pandas](https://pandas.pydata.org/): The pandas library for data manipulation and analysis in Python.\n- [matplotlib](https://matplotlib.org/): The matplotlib library for data visualization in Python.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudacity-machinelearning-internship%2Fpolynomial-regression","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fudacity-machinelearning-internship%2Fpolynomial-regression","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudacity-machinelearning-internship%2Fpolynomial-regression/lists"}