{"id":24605957,"url":"https://github.com/udacity-machinelearning-internship/perceptrons-as-logical-operators","last_synced_at":"2025-03-18T10:41:08.560Z","repository":{"id":239880189,"uuid":"800871409","full_name":"Udacity-MachineLearning-Internship/Perceptrons-as-Logical-Operators","owner":"Udacity-MachineLearning-Internship","description":"Applying Perceptrons as Logical Operators using Pandas","archived":false,"fork":false,"pushed_at":"2024-05-17T03:39:31.000Z","size":6,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-21T08:24:10.219Z","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/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":"2024-05-15T06:50:04.000Z","updated_at":"2024-12-17T20:45:51.000Z","dependencies_parsed_at":"2024-05-17T04:33:53.465Z","dependency_job_id":"0b6cdd1c-b13e-4a77-93d3-781cf616aa7c","html_url":"https://github.com/Udacity-MachineLearning-Internship/Perceptrons-as-Logical-Operators","commit_stats":null,"previous_names":["barasedih11/perceptrons-as-logical-operators","udacity-machinelearning-internship/perceptrons-as-logical-operators"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPerceptrons-as-Logical-Operators","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPerceptrons-as-Logical-Operators/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPerceptrons-as-Logical-Operators/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FPerceptrons-as-Logical-Operators/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Udacity-MachineLearning-Internship","download_url":"https://codeload.github.com/Udacity-MachineLearning-Internship/Perceptrons-as-Logical-Operators/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244206607,"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":[],"created_at":"2025-01-24T16:49:58.714Z","updated_at":"2025-03-18T10:41:08.537Z","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![Perceptrons_As_Logical_Operators](https://github.com/BaraSedih11/Perceptrons-as-Logical-Operators/assets/98843912/59e128bc-cf35-48c0-80e0-3d5bd3afb43e)\n\n   ![GitHub repo size](https://img.shields.io/github/repo-size/BaraSedih11/Perceptrons-as-Logical-Operators) ![GitHub repo file count (file type)](https://img.shields.io/github/directory-file-count/BaraSedih11/Perceptrons-as-Logical-Operators) [![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/Perceptrons-as-Logical-Operators/main)\n[![Version](https://img.shields.io/badge/version-v1.0.0-blue)](https://github.com/BaraSedih11/Perceptrons-as-Logical-Operators/releases/tag/v1.0.0)\n[![Contributors](https://img.shields.io/github/contributors/BaraSedih11/Perceptrons-as-Logical-Operators)](https://github.com/BaraSedih11/Perceptrons-as-Logical-Operators/graphs/contributors)\n![GitHub pull requests](https://img.shields.io/github/issues-pr-raw/BaraSedih11/Perceptrons-as-Logical-Operators)\n\u003c!-- ![GitHub issues](https://img.shields.io/github/issues-raw/BaraSedih11/Bookstore)  --\u003e\n\u003c/div\u003e\n\n\nThis repository contains an implementation of Perceptrons as Logical Operators using Pandas.\n\n## Overview\n\nIn this repository, we'll see one of the many great applications of perceptrons. As logical operators! You'll have the chance to create the perceptrons for the most common of these, the AND, OR, and NOT operators. And then, we'll see what to do about the elusive XOR operator. Let's dive in!\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- pandas\n\nYou can install these libraries using pip:\n\n```bash\npip install pandas\n\n```\n\n## Usage\n\n1. Clone this repository to your local machine:\n\n```bash\ngit clone https://github.com/BaraSedih11/Perceptrons-as-Logical-Operators.git\n```\n\n2. Navigate to the repository directory:\n\n```bash\ncd perceptronAsLogicalOperators\n```\n\n3. Open and run the Jupyter Notebook `PerceptronAsLogicalOperators.ipynb` using Jupyter Notebook or JupyterLab.\n\n4. Follow along with the code and comments in the notebook to understand how perceptron algorithms as logical operators is implemented using Python.\n\n\n## Acknowledgements\n\n- [pandas](https://pandas.pydata.org/): The pandas library for data manipulation and analysis in Python.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudacity-machinelearning-internship%2Fperceptrons-as-logical-operators","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fudacity-machinelearning-internship%2Fperceptrons-as-logical-operators","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudacity-machinelearning-internship%2Fperceptrons-as-logical-operators/lists"}