Some reference Kaggle competitions from the past are:
\n\nMercari Price Suggestion Challenge
\n\nToxic Comment Classification Challenge
\n\nIf you think of any other good reference competitions from the past, please add them in the comments. Happy Kaggling.!
", "messages": [ { "id": "416858", "postDate": "11/07/2018 11:25:13", "content": "Some reference Kaggle competitions from the past are:
\n\nMercari Price Suggestion Challenge
\n\nToxic Comment Classification Challenge
\n\nIf you think of any other good reference competitions from the past, please add them in the comments. Happy Kaggling.!
", "rawMarkdown": "Some reference Kaggle competitions from the past are:\n \n[Mercari Price Suggestion Challenge][1] \n\n - A kernels only competition which involves text data\n - Several winning kernels are available in the kernels page of the competition which could be used for getting new ideas to improve the model / speed up the computation\n\n[Quora Question Pairs][2]\n \n- Previous Kaggle competition hosted by Quora\n- There was some leakage in the data but lot of useful features can be seen in the discussion forums / kernels\n\n[Toxic Comment Classification Challenge][3]\n \n- Objective is to predict different types of of toxicity like threats, obscenity, insults, and identity-based hate \n- Here also we are trying to predict different types of insincere questions and so might be a helpful one to refer to.\n\nIf you think of any other good reference competitions from the past, please add them in the comments. Happy Kaggling.! \n\n\n [1]: https://www.kaggle.com/c/mercari-price-suggestion-challenge\n [2]: https://www.kaggle.com/c/quora-question-pairs\n [3]: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge", "votes": null }, { "id": "416963", "postDate": "11/07/2018 14:34:31", "content": "Thanks for compiling the list!
\n\nHere are some winning solutions from them:
\n\nToxic: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/72597
\n\nMercari: https://www.kaggle.com/c/mercari-price-suggestion-challenge/discussion/49819#287889
\n\nQuora question pair: https://www.kaggle.com/c/quora-question-pairs/discussion/34325
\n\nAs well as your awesome list: https://www.kaggle.com/sudalairajkumar/winning-solutions-of-kaggle-competitions
", "rawMarkdown": "Thanks for compiling the list! \n\nHere are some winning solutions from them:\n\nToxic: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/72597\n\nMercari: https://www.kaggle.com/c/mercari-price-suggestion-challenge/discussion/49819#287889\n\nQuora question pair: https://www.kaggle.com/c/quora-question-pairs/discussion/34325\n\n\nAs well as your awesome list: https://www.kaggle.com/sudalairajkumar/winning-solutions-of-kaggle-competitions", "votes": null }, { "id": "417044", "postDate": "11/07/2018 16:41:42", "content": "I'd add https://www.kaggle.com/c/spooky-author-identification with lots of tutorials on NLP in a form of Kernels.
", "rawMarkdown": "I'd add https://www.kaggle.com/c/spooky-author-identification with lots of tutorials on NLP in a form of Kernels.", "votes": null }, { "id": "417070", "postDate": "11/07/2018 17:32:37", "content": "Thanks @shujian and @kashnitsky for the additions.
\n\nSome more interesting kernels are:
\n\nMany thanks!
", "rawMarkdown": "Many thanks!", "votes": null }, { "id": "445761", "postDate": "12/27/2018 03:09:51", "content": "Thanks so much for putting this together!
", "rawMarkdown": "Thanks so much for putting this together!", "votes": null }, { "id": "1126315", "postDate": "12/25/2020 14:13:59", "content": "Thanks macha
", "rawMarkdown": "Thanks macha", "votes": null }, { "id": "1307880", "postDate": "05/14/2021 18:16:39", "content": "Many Thanks
", "rawMarkdown": "Many Thanks", "votes": null } ], "comments": [ { "id": 1126315, "author_name": "abdullllkhan", "author_url": "", "post_date": "12/25/2020 14:13:59", "content": "Thanks macha
", "votes": null, "replies": [] }, { "id": 1307880, "author_name": "amardata", "author_url": "", "post_date": "05/14/2021 18:16:39", "content": "Many Thanks
", "votes": null, "replies": [] }, { "id": 416963, "author_name": "shujian", "author_url": "", "post_date": "11/07/2018 14:34:31", "content": "Thanks for compiling the list!
\n\nHere are some winning solutions from them:
\n\nToxic: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/72597
\n\nMercari: https://www.kaggle.com/c/mercari-price-suggestion-challenge/discussion/49819#287889
\n\nQuora question pair: https://www.kaggle.com/c/quora-question-pairs/discussion/34325
\n\nAs well as your awesome list: https://www.kaggle.com/sudalairajkumar/winning-solutions-of-kaggle-competitions
", "votes": null, "replies": [] }, { "id": 417044, "author_name": "kashnitsky", "author_url": "", "post_date": "11/07/2018 16:41:42", "content": "I'd add https://www.kaggle.com/c/spooky-author-identification with lots of tutorials on NLP in a form of Kernels.
", "votes": null, "replies": [] }, { "id": 417070, "author_name": "sudalairajkumar", "author_url": "", "post_date": "11/07/2018 17:32:37", "content": "Thanks @shujian and @kashnitsky for the additions.
\n\nSome more interesting kernels are:
\n\nMany thanks!
", "votes": null, "replies": [] }, { "id": 445761, "author_name": "johnjohnjohn", "author_url": "", "post_date": "12/27/2018 03:09:51", "content": "Thanks so much for putting this together!
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "416858": "Some reference Kaggle competitions from the past are:\n \n[Mercari Price Suggestion Challenge][1] \n\n - A kernels only competition which involves text data\n - Several winning kernels are available in the kernels page of the competition which could be used for getting new ideas to improve the model / speed up the computation\n\n[Quora Question Pairs][2]\n \n- Previous Kaggle competition hosted by Quora\n- There was some leakage in the data but lot of useful features can be seen in the discussion forums / kernels\n\n[Toxic Comment Classification Challenge][3]\n \n- Objective is to predict different types of of toxicity like threats, obscenity, insults, and identity-based hate \n- Here also we are trying to predict different types of insincere questions and so might be a helpful one to refer to.\n\nIf you think of any other good reference competitions from the past, please add them in the comments. Happy Kaggling.! \n\n\n [1]: https://www.kaggle.com/c/mercari-price-suggestion-challenge\n [2]: https://www.kaggle.com/c/quora-question-pairs\n [3]: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge", "416963": "Thanks for compiling the list! \n\nHere are some winning solutions from them:\n\nToxic: https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/72597\n\nMercari: https://www.kaggle.com/c/mercari-price-suggestion-challenge/discussion/49819#287889\n\nQuora question pair: https://www.kaggle.com/c/quora-question-pairs/discussion/34325\n\n\nAs well as your awesome list: https://www.kaggle.com/sudalairajkumar/winning-solutions-of-kaggle-competitions", "417044": "I'd add https://www.kaggle.com/c/spooky-author-identification with lots of tutorials on NLP in a form of Kernels.", "417070": "Thanks @shujian and @kashnitsky for the additions. \n\nSome more interesting kernels are:\n\n 1. [Spell Checker using Word2vec](https://www.kaggle.com/cpmpml/spell-checker-using-word2vec)\n 2. [The Importance of Cleaning Text](https://www.kaggle.com/currie32/the-importance-of-cleaning-text)\n 3. [Do Pretrained Embeddings Give You The Extra Edge?](https://www.kaggle.com/sbongo/do-pretrained-embeddings-give-you-the-extra-edge)\n 4. [NB-SVM strong linear baseline](https://www.kaggle.com/jhoward/nb-svm-strong-linear-baseline)\n 5. [WordBatch FM FTRL](https://www.kaggle.com/anttip/wordbatch-1-3-3-fm-ftrl-lb-0-9812)", "424668": "Many thanks!", "445761": "Thanks so much for putting this together!", "1126315": "Thanks macha", "1307880": "Many Thanks" }, "source": "meta" }