{"id":24605969,"url":"https://github.com/udacity-machinelearning-internship/diabetescasestudy","last_synced_at":"2025-03-18T10:41:09.550Z","repository":{"id":241225981,"uuid":"804664860","full_name":"Udacity-MachineLearning-Internship/DiabetesCaseStudy","owner":"Udacity-MachineLearning-Internship","description":"Implementing several models with visualizations to putting all togother in Training and Tuning","archived":false,"fork":false,"pushed_at":"2024-05-29T01:44:38.000Z","size":1692,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-21T08:24:10.248Z","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":"2024-05-23T03:02:35.000Z","updated_at":"2024-12-17T20:43:30.000Z","dependencies_parsed_at":"2025-01-21T08:34:36.965Z","dependency_job_id":null,"html_url":"https://github.com/Udacity-MachineLearning-Internship/DiabetesCaseStudy","commit_stats":null,"previous_names":["barasedih11/diabetescasestudy","udacity-machinelearning-internship/diabetescasestudy"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FDiabetesCaseStudy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FDiabetesCaseStudy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FDiabetesCaseStudy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Udacity-MachineLearning-Internship%2FDiabetesCaseStudy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Udacity-MachineLearning-Internship","download_url":"https://codeload.github.com/Udacity-MachineLearning-Internship/DiabetesCaseStudy/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244206617,"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":"2025-01-24T16:49:59.020Z","updated_at":"2025-03-18T10:41:09.527Z","avatar_url":"https://github.com/Udacity-MachineLearning-Internship.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=center\u003e\n  \n  ![Diabetes_Case_Study](https://github.com/BaraSedih11/DiabetesCaseStudy/assets/98843912/90679af3-217d-44c5-a387-9acc43d002d1)\n\n\n   ![GitHub repo size](https://img.shields.io/github/repo-size/BaraSedih11/DiabetesCaseStudy) ![GitHub repo file count (file type)](https://img.shields.io/github/directory-file-count/BaraSedih11/DiabetesCaseStudy) [![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/DiabetesCaseStudy/main)\n[![Version](https://img.shields.io/badge/version-v1.0.0-blue)](https://github.com/BaraSedih11/DiabetesCaseStudy/releases/tag/v1.0.0)\n[![Contributors](https://img.shields.io/github/contributors/BaraSedih11/DiabetesCaseStudy)](https://github.com/BaraSedih11/DiabetesCaseStudy/graphs/contributors)\n![GitHub pull requests](https://img.shields.io/github/issues-pr-raw/BaraSedih11/DiabetesCaseStudy)\n  \n\u003c/div\u003e\n\nThis repository contains a comprehensive analysis and model implementation for predicting diabetes using machine learning techniques. It includes data preprocessing, model training, hyperparameter tuning, and evaluation of various regression metrics.\n\n## Introduction\nThis project aims to identify the best estimators and features for predicting diabetes outcomes based on the provided dataset. The analysis is performed using Python and several data science libraries.\n\n\n## Contents\n\n- `Regression Metrics.ipynb`: Jupyter Notebook containing the implementation of Random Forest using Python.\n- `README.md`: This file providing an overview of the repository.\n- `diabetes.csv`: This is the working dataset.\n\n\n## Requirements\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* seaborn\nYou can install these libraries using pip:\n\n```bash\npip install numpy pandas scikit-learn matplotlib seaborn\n```\n\n## Usage\n\n1. Clone this repository to your local machine:\n\n```bash\ngit clone https://github.com/BaraSedih11/DiabetesCaseStudy.git\n```\n\n2. Navigate to the repository directory:\n\n```bash\ncd DiabetesCaseStudy\n```\n\n3. Open and run the Jupyter Notebook `jupyter notebook Regression\\ Metrics.ipynb`.\n\n4. Follow along with the code and comments in the notebook to understand the implementation of regression metrics, model training, and hyperparameter tuning using Python.\n\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- [seaborn](https://seaborn.pydata.org/): The seaborn library for data visualization in Python.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudacity-machinelearning-internship%2Fdiabetescasestudy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fudacity-machinelearning-internship%2Fdiabetescasestudy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fudacity-machinelearning-internship%2Fdiabetescasestudy/lists"}