{
  "id": 56706,
  "title": "Did anyone use Dask or Ray?",
  "url": "/competitions/talkingdata-adtracking-fraud-detection/discussion/56706",
  "author_name": "Silverback",
  "post_date": "2018-05-13T21:26:01.231000",
  "votes": 0,
  "comment_count": 0,
  "views": 0,
  "content": "<p>I saw a lot of people doing <a href=\"https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/54948\">work around</a> in <a href=\"https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/55379\">Pandas</a> to try and handle Out of Memory errors. <a href=\"https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/56571\">Others</a> used numpy to good effect to speed up running code and reduce the need for swap space.</p>\n\n<p>Seeing as both Dask and Ray are designed for either, speeding up computation or reducing memory usage, did anyone use these to run their final solutions?</p>",
  "messages": [
    {
      "id": 328281,
      "postDate": "2018-05-13T21:26:01.230Z",
      "content": "<p>I saw a lot of people doing <a href=\"https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/54948\">work around</a> in <a href=\"https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/55379\">Pandas</a> to try and handle Out of Memory errors. <a href=\"https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/56571\">Others</a> used numpy to good effect to speed up running code and reduce the need for swap space.</p>\n\n<p>Seeing as both Dask and Ray are designed for either, speeding up computation or reducing memory usage, did anyone use these to run their final solutions?</p>",
      "rawMarkdown": "I saw a lot of people doing [work around][1] in [Pandas][2] to try and handle Out of Memory errors. [Others][3] used numpy to good effect to speed up running code and reduce the need for swap space.\n\nSeeing as both Dask and Ray are designed for either, speeding up computation or reducing memory usage, did anyone use these to run their final solutions?\n\n\n  [1]: https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/54948\n  [2]: https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/55379\n  [3]: https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/56571"
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "328281": "I saw a lot of people doing [work around][1] in [Pandas][2] to try and handle Out of Memory errors. [Others][3] used numpy to good effect to speed up running code and reduce the need for swap space.\n\nSeeing as both Dask and Ray are designed for either, speeding up computation or reducing memory usage, did anyone use these to run their final solutions?\n\n\n  [1]: https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/54948\n  [2]: https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/55379\n  [3]: https://www.kaggle.com/c/talkingdata-adtracking-fraud-detection/discussion/56571"
  }
}