{
  "id": 153389,
  "title": "[Info]: Text Augmentation",
  "url": "/competitions/jigsaw-multilingual-toxic-comment-classification/discussion/153389",
  "author_name": "",
  "post_date": "2020-05-24T14:19:09.012653100Z",
  "votes": 15,
  "comment_count": 1,
  "views": 0,
  "content": "<p>A list of few promising approaches for NLP augmentation.</p>\n\n<ul>\n<li><p><a href=\"https://arxiv.org/pdf/1901.11196v2.pdf\"><strong>EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks</strong></a> - <a href=\"https://github.com/jasonwei20/eda_nlp\"><strong>Code</strong></a></p></li>\n<li><p><a href=\"https://www.kaggle.com/shonenkov/nlp-albumentations/notebook\">NLP Albumentations</a> - demonstrated by <a href=\"https://www.kaggle.com/shonenkov\">Alex Shonenkov</a></p></li>\n<li><a href=\"https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/48038\"><strong>A simple technique for extending dataset</strong></a> by <a href=\"https://www.kaggle.com/pavelost\">Pavel Ostyakov</a></li>\n<li><a href=\"https://github.com/jsvine/markovify\">A simple, extensible Markov chain generator.</a> - informed by <a href=\"https://www.kaggle.com/jpmiller/augmenting-the-data\">JohnM</a></li>\n<li><a href=\"https://github.com/makcedward/nlpaug\">Data augmentation for NLP</a> (GitHub)</li>\n</ul>",
  "messages": [
    {
      "id": "859525",
      "postDate": "05/24/2020 14:19:09",
      "content": "<p>A list of few promising approaches for NLP augmentation.</p>\n\n<ul>\n<li><p><a href=\"https://arxiv.org/pdf/1901.11196v2.pdf\"><strong>EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks</strong></a> - <a href=\"https://github.com/jasonwei20/eda_nlp\"><strong>Code</strong></a></p></li>\n<li><p><a href=\"https://www.kaggle.com/shonenkov/nlp-albumentations/notebook\">NLP Albumentations</a> - demonstrated by <a href=\"https://www.kaggle.com/shonenkov\">Alex Shonenkov</a></p></li>\n<li><a href=\"https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/48038\"><strong>A simple technique for extending dataset</strong></a> by <a href=\"https://www.kaggle.com/pavelost\">Pavel Ostyakov</a></li>\n<li><a href=\"https://github.com/jsvine/markovify\">A simple, extensible Markov chain generator.</a> - informed by <a href=\"https://www.kaggle.com/jpmiller/augmenting-the-data\">JohnM</a></li>\n<li><a href=\"https://github.com/makcedward/nlpaug\">Data augmentation for NLP</a> (GitHub)</li>\n</ul>",
      "rawMarkdown": "A list of few promising approaches for NLP augmentation.\n\n- [**EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks**](https://arxiv.org/pdf/1901.11196v2.pdf) - [**Code**](https://github.com/jasonwei20/eda_nlp)\n\n- [NLP Albumentations](https://www.kaggle.com/shonenkov/nlp-albumentations/notebook) - demonstrated by [Alex Shonenkov](https://www.kaggle.com/shonenkov)\n- [**A simple technique for extending dataset**](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/48038) by [Pavel Ostyakov](https://www.kaggle.com/pavelost)\n- [A simple, extensible Markov chain generator.](https://github.com/jsvine/markovify) - informed by [JohnM](https://www.kaggle.com/jpmiller/augmenting-the-data)\n- [Data augmentation for NLP](https://github.com/makcedward/nlpaug) (GitHub)",
      "votes": null
    },
    {
      "id": "988828",
      "postDate": "08/28/2020 10:09:39",
      "content": "<p>Regarding EDA : <br>\nClearly Explained Kernal with examples<br>\n<a href=\"https://www.kaggle.com/swarajshinde/eda-data-augmentation-techniques-for-text-nlp\" target=\"_blank\">https://www.kaggle.com/swarajshinde/eda-data-augmentation-techniques-for-text-nlp</a></p>",
      "rawMarkdown": "Regarding EDA : \nClearly Explained Kernal with examples\nhttps://www.kaggle.com/swarajshinde/eda-data-augmentation-techniques-for-text-nlp",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 988828,
      "author_name": "swarajshinde",
      "author_url": "",
      "post_date": "08/28/2020 10:09:39",
      "content": "<p>Regarding EDA : <br>\nClearly Explained Kernal with examples<br>\n<a href=\"https://www.kaggle.com/swarajshinde/eda-data-augmentation-techniques-for-text-nlp\" target=\"_blank\">https://www.kaggle.com/swarajshinde/eda-data-augmentation-techniques-for-text-nlp</a></p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "859525": "A list of few promising approaches for NLP augmentation.\n\n- [**EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks**](https://arxiv.org/pdf/1901.11196v2.pdf) - [**Code**](https://github.com/jasonwei20/eda_nlp)\n\n- [NLP Albumentations](https://www.kaggle.com/shonenkov/nlp-albumentations/notebook) - demonstrated by [Alex Shonenkov](https://www.kaggle.com/shonenkov)\n- [**A simple technique for extending dataset**](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/48038) by [Pavel Ostyakov](https://www.kaggle.com/pavelost)\n- [A simple, extensible Markov chain generator.](https://github.com/jsvine/markovify) - informed by [JohnM](https://www.kaggle.com/jpmiller/augmenting-the-data)\n- [Data augmentation for NLP](https://github.com/makcedward/nlpaug) (GitHub)",
    "988828": "Regarding EDA : \nClearly Explained Kernal with examples\nhttps://www.kaggle.com/swarajshinde/eda-data-augmentation-techniques-for-text-nlp"
  },
  "source": "meta"
}