{"id":15632716,"url":"https://github.com/hunkim/kagglezerotoall","last_synced_at":"2026-03-27T04:56:37.498Z","repository":{"id":90561513,"uuid":"86294127","full_name":"hunkim/KaggleZeroToAll","owner":"hunkim","description":"Kaggle problem solving","archived":false,"fork":false,"pushed_at":"2017-08-14T22:32:03.000Z","size":8082,"stargazers_count":168,"open_issues_count":1,"forks_count":71,"subscribers_count":21,"default_branch":"master","last_synced_at":"2024-11-26T05:51:53.969Z","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/hunkim.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}},"created_at":"2017-03-27T05:20:13.000Z","updated_at":"2024-06-09T07:36:45.000Z","dependencies_parsed_at":null,"dependency_job_id":"64b14dcc-cc41-4930-b3a2-fbf516b0f08b","html_url":"https://github.com/hunkim/KaggleZeroToAll","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/hunkim%2FKaggleZeroToAll","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hunkim%2FKaggleZeroToAll/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hunkim%2FKaggleZeroToAll/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hunkim%2FKaggleZeroToAll/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hunkim","download_url":"https://codeload.github.com/hunkim/KaggleZeroToAll/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":230445926,"owners_count":18227060,"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":"2024-10-03T10:45:05.306Z","updated_at":"2026-03-27T04:56:32.461Z","avatar_url":"https://github.com/hunkim.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# KaggleZeroToAll\n\nAfter knowing basics of machine learning, deep learning, and TensorFlow/Keras, what's the next?\n\nKaggle provides many interesting problems for machine learning experts. \nThis repository hosts interesting Kaggle problems and show how to solve these problems using decent deep learning models.\n\n## Kaggle problem directory naming \nk0-00-short-title\n\n* Difficulty (k0, k1, ... k9): \n    - 0: easy\n    - 5: normal\n    - 9: very difficult\n* k0-XX: 00 serial number\n* short-title: title for the Kaggle data\n* put `.py`, `.ipynb`, and data files in the directory\n    - If data files are large, you can create a script. Please check [this](k0-01-titanic/data_download.sh)\n\n## Content of each file\nPlease see k0-00-template.ipynb\n\n* Kaggle name\n* dataset/problem description\n* loading data\n* model to solve the problem\n* results\n* future work and exercises\n\n## Dependencies for Kaggle Utils (optional)\n```\nrequests==2.13.0\nbeautifulsoup4==4.6.0\n```\nor \n```bash\npip install -r requirements.txt\n```\n\n## Kaggle Utils (optional)\n* `kaggle_download.py`: Kaggle download script\n    1. Create **kaggle.ini**\n        - Copy `kaggle.ini.sample` and name it `kaggle.ini`\n        - Fill out your `username` and `password` in kaggle.ini\n    2. **Accept the agreement term** in Kaggle website\n        - Click the download button on the competition main site\n    3. Find a **competition name**\n        * Competition name can be found in the URL\n        * For example, if the url is https://www.kaggle.com/c/digit-recognizer,  \n          then the competition name is **digit-recognizer**\n    3. In terminal,\n    ```bash\n    # python kaggle_download.py competition-name --destination path/to/save/dataset\n    # Example:\n    $ python kaggle_download.py digit-recognizer --destination k0-01-mnist/input\n    ```\n\n* `kaggle_submit.py`: Kaggle submission script\n    1. You can also submit your submission\n    2. In terminal,\n    ```bash \n    # python kaggle_submit.py competition-name /path/to/submission.csv -m \"Submission message\"\n    # Example:\n    python kaggle_submit.py digit-recognizer k0-01-mnist/submission.csv -m \"First Submission\"\n    ```\n\n## Tests\n\n```bash\npy.test\n```\n\n ## Contributions\n We welcome any contributions including writing issues and sending pull requests.\n \n ## References (Thanks to the TF-KR user group)\n * https://www.quora.com/What-Kaggle-competitions-should-a-beginner-start-with-1\n * http://ndres.me/kaggle-past-solutions/\n * http://www.chioka.in/kaggle-competition-solutions/\n * http://analyticscosm.com/learning-predictive-analytics-kaggle-competition-solutions/\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhunkim%2Fkagglezerotoall","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhunkim%2Fkagglezerotoall","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhunkim%2Fkagglezerotoall/lists"}