{"id":19771786,"url":"https://github.com/haimgoldfisher/data_sience_intro_final_project","last_synced_at":"2026-04-16T05:04:32.705Z","repository":{"id":119535027,"uuid":"346322748","full_name":"haimgoldfisher/Data_Sience_Intro_Final_Project","owner":"haimgoldfisher","description":"Final project of the Data Sience Intro course, Ariel university.","archived":false,"fork":false,"pushed_at":"2021-03-29T15:15:11.000Z","size":28083,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-28T11:30:20.605Z","etag":null,"topics":["bayes","classification","decision-trees","diamond","kaggle","knn-classification","linear-regression","logistic-regression","numpy","pandas","regression","scikitlearn-machine-learning","sklearn","wine"],"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/haimgoldfisher.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":"2021-03-10T10:50:54.000Z","updated_at":"2021-05-06T07:55:16.000Z","dependencies_parsed_at":null,"dependency_job_id":"ab923e3a-b852-4f23-a6fd-bb3d270103f4","html_url":"https://github.com/haimgoldfisher/Data_Sience_Intro_Final_Project","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/haimgoldfisher/Data_Sience_Intro_Final_Project","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haimgoldfisher%2FData_Sience_Intro_Final_Project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haimgoldfisher%2FData_Sience_Intro_Final_Project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haimgoldfisher%2FData_Sience_Intro_Final_Project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haimgoldfisher%2FData_Sience_Intro_Final_Project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/haimgoldfisher","download_url":"https://codeload.github.com/haimgoldfisher/Data_Sience_Intro_Final_Project/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haimgoldfisher%2FData_Sience_Intro_Final_Project/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31872036,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-15T15:24:51.572Z","status":"online","status_checked_at":"2026-04-16T02:00:06.042Z","response_time":69,"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":["bayes","classification","decision-trees","diamond","kaggle","knn-classification","linear-regression","logistic-regression","numpy","pandas","regression","scikitlearn-machine-learning","sklearn","wine"],"created_at":"2024-11-12T05:04:11.144Z","updated_at":"2026-04-16T05:04:32.700Z","avatar_url":"https://github.com/haimgoldfisher.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Sience Intro Course - Final Project\n\n---------\n\n### Part I : Probability, Bayes' Theorem\n\nAnswers to questions on various topics in probability.\nIncluding conditional probability, Bayes' theorem and expected value.\n\n---------\n\n### Part II : Programming Exercises\n\nQuestions that focus on programming, such as converting decimal numbers.\nAlso, a variety of questions about the dataset 'cast': panads library, ploting, groupby and more.\n\n---------\n\n### Part III : Machine Learning (included two notebooks):\n\n---------\n\n### NoteBook 1: Classification\n\nIf you're not a color blind, you'll probably think this model is a kind of silly. Because the next model is going to reveal something that is not so hard to notice. In this model we are going to find out if it is possible to know the color of a wine (red or white) based on it's data. I think it may sound simple, however it can give us an explanation for whether there is a significant difference between red and white wine, or not.\n\nLink to kaggle: https://www.kaggle.com/haimgoldfisher/wine-type-classifier\n\n---------\n\n### NoteBook 2: Regression\n\nFamiliar with the well-known phrase \"Diamonds are forever\"? Did you ever hear Marilyn Monroe's song \"Diamonds are a girl's best friend\"? So much has been written and said about this shiny crystal. But there is one thing that everyone agrees on, people just love diamonds. Have you ever wondered how the price of a diamond can be estimated? In the above model we will try to predict the price of a diamond based on its data. You may not need to be such a great expert to understand how much it is worth paying for a diamond ring.\n\nLink to kaggle: https://www.kaggle.com/haimgoldfisher/diamond-price-prediction\n\n---------\n\n@ Haim Goldfisher\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhaimgoldfisher%2Fdata_sience_intro_final_project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhaimgoldfisher%2Fdata_sience_intro_final_project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhaimgoldfisher%2Fdata_sience_intro_final_project/lists"}