{"id":18110077,"url":"https://github.com/alexattia/Data-Science-Projects","last_synced_at":"2025-03-29T17:32:14.642Z","repository":{"id":38359675,"uuid":"58724357","full_name":"alexattia/Data-Science-Projects","owner":"alexattia","description":"DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.","archived":false,"fork":false,"pushed_at":"2023-01-13T05:40:45.000Z","size":11338,"stargazers_count":929,"open_issues_count":7,"forks_count":450,"subscribers_count":50,"default_branch":"master","last_synced_at":"2024-11-01T00:06:21.571Z","etag":null,"topics":["challenge","hackerrank","kaggle","machine-learning","python"],"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/alexattia.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}},"created_at":"2016-05-13T09:36:04.000Z","updated_at":"2024-10-27T05:47:22.000Z","dependencies_parsed_at":"2023-02-09T14:32:49.585Z","dependency_job_id":null,"html_url":"https://github.com/alexattia/Data-Science-Projects","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexattia%2FData-Science-Projects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexattia%2FData-Science-Projects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexattia%2FData-Science-Projects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alexattia%2FData-Science-Projects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alexattia","download_url":"https://codeload.github.com/alexattia/Data-Science-Projects/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246220794,"owners_count":20742847,"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":["challenge","hackerrank","kaggle","machine-learning","python"],"created_at":"2024-11-01T00:02:06.944Z","updated_at":"2025-03-29T17:32:12.898Z","avatar_url":"https://github.com/alexattia.png","language":"Jupyter Notebook","readme":"# Online-Challenge\nChallenge submitted on HackerRank and Kaggle.\n\nAlgorithm challenges are made on HackerRank using Python.\n\nData Science and Machine Learning challenges are made on Kaggle using Python too. \n\n## [Kaggle Bike Sharing](https://github.com/alexattia/Data-Science-Projects/tree/master/KaggleBikeSharing)\nThe goal of this challenge is to build a model that predicts the count of bike shared, exclusively based on contextual features. The first part of this challenge was aimed to understand, to analyse and to process those dataset. I wanted to produce meaningful information with plots. The second part was to build a model and use a Machine Learning library in order to predict the count.\n\n--\u003e[French Explanations PDF](https://github.com/alexattia/Data-Science-Projects/blob/master/KaggleBikeSharing/Kaggle_BikeSharing_Explanations_French.pdf)\n\n## [Twitter Parsing](https://github.com/alexattia/Data-Science-Projects/tree/master/TwitterParsing)\n\nI've recently discovered the Chris Albon Machine Learning flash cards and I want to download those flash cards but the official Twitter API has a limit rate of 2 weeks old tweets so I had to find a way to bypass this limitation : use Selenium and PhantomJS.  \nPurpose of this project : Check every 2 hours, if he posted new flash cards. In this case, download them and send me a summary email.\n\n## [Face Recognition](https://github.com/alexattia/Data-Science-Projects/tree/master/FaceRecognition)\n\nModern face recognition with deep learning and HOG algorithm. Using dlib C++ library, I have a quick face recognition tool using few pictures (20 per person).\n\n## [Playing with Soccer data](https://github.com/alexattia/Data-Science-Projects/tree/master/KaggleSoccer)\n\nAs a soccer fan and a data passionate, I wanted to play and analyze with soccer data.  \nI don't know currently what's the aim of this project but I will parse data from diverse websites, for differents teams and differents players. \n\n## [NYC Taxi Trips](https://github.com/alexattia/Data-Science-Projects/tree/master/KaggleTaxiTrip)\n\nKaggle playground to predict the total ride duration of taxi trips in New York City. \n\n## [Kaggle Understanding the Amazon from Space](https://github.com/alexattia/Data-Science-Projects/tree/master/KaggleAmazon) \nUse satellite data to track the human footprint in the Amazon rainforest.  \nDeep Learning model (using Keras) to label satellite images.\n\n## [Predicting IMDB movie rating](https://github.com/alexattia/Data-Science-Projects/tree/master/KaggleMovieRating)\nProject inspired by Chuan Sun [work](https://www.kaggle.com/deepmatrix/imdb-5000-movie-dataset)  \nHow can we tell the greatness of a movie ?  \nScrapping and Machine Learning  ","funding_links":[],"categories":["Uncategorized","100 + 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗟𝗶𝘀𝘁 𝘄𝗶𝘁𝗵 𝗰𝗼𝗱𝗲"],"sub_categories":["Uncategorized"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexattia%2FData-Science-Projects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falexattia%2FData-Science-Projects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexattia%2FData-Science-Projects/lists"}