{
  "id": 113642,
  "title": "Google Time Series Forecasting Solutions",
  "url": "/competitions/ashrae-energy-prediction/discussion/113642",
  "author_name": "",
  "post_date": "2019-10-21T03:24:59.606009100Z",
  "votes": 6,
  "comment_count": 2,
  "views": 0,
  "content": "<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd085caeab66fe5a2d9cb3d4e03ab8e57%2Fforcast.png?generation=1571628252023548&amp;alt=media\" alt=\"\"></p>\n\n<p>In this discussion, I had tried to collect top solutions for the  <strong>Google Web Traffic Time Series Forecasting : Forecast future traffic to Wikipedia pages</strong>. This old competition present a <strong>Time Series Forecasting</strong> problem which may help some people to improve their solution. You can add any helpful content to help each other.</p>\n\n<p><a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43795\">1st place solution</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39370\">6th-Place Solution Overview</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43727#latest-492742\">8th place with Kalman filters\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39876#latest-244632\">3rd place [after the first update] solution is based on kNN\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43621#latest-245353\">7th place solution\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43603#latest-357348\">Description of 5th place solution\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43569#latest-244681\">30th Place Approach and Lessons Learned\n</a></p>",
  "messages": [
    {
      "id": "653840",
      "postDate": "10/21/2019 03:24:59",
      "content": "<p><img src=\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd085caeab66fe5a2d9cb3d4e03ab8e57%2Fforcast.png?generation=1571628252023548&amp;alt=media\" alt=\"\"></p>\n\n<p>In this discussion, I had tried to collect top solutions for the  <strong>Google Web Traffic Time Series Forecasting : Forecast future traffic to Wikipedia pages</strong>. This old competition present a <strong>Time Series Forecasting</strong> problem which may help some people to improve their solution. You can add any helpful content to help each other.</p>\n\n<p><a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43795\">1st place solution</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39370\">6th-Place Solution Overview</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43727#latest-492742\">8th place with Kalman filters\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39876#latest-244632\">3rd place [after the first update] solution is based on kNN\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43621#latest-245353\">7th place solution\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43603#latest-357348\">Description of 5th place solution\n</a>\n<a href=\"https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43569#latest-244681\">30th Place Approach and Lessons Learned\n</a></p>",
      "rawMarkdown": "![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd085caeab66fe5a2d9cb3d4e03ab8e57%2Fforcast.png?generation=1571628252023548&amp;alt=media)\n\nIn this discussion, I had tried to collect top solutions for the  **Google Web Traffic Time Series Forecasting : Forecast future traffic to Wikipedia pages**. This old competition present a **Time Series Forecasting** problem which may help some people to improve their solution. You can add any helpful content to help each other.\n\n[1st place solution](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43795)\n[6th-Place Solution Overview](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39370)\n[8th place with Kalman filters\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43727#latest-492742)\n[3rd place [after the first update] solution is based on kNN\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39876#latest-244632)\n[7th place solution\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43621#latest-245353)\n[Description of 5th place solution\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43603#latest-357348)\n[30th Place Approach and Lessons Learned\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43569#latest-244681)",
      "votes": null
    },
    {
      "id": "677718",
      "postDate": "11/20/2019 14:20:15",
      "content": "<p>Thanks. Those are good reads.</p>",
      "rawMarkdown": "Thanks. Those are good reads.",
      "votes": null
    },
    {
      "id": "677769",
      "postDate": "11/20/2019 15:14:34",
      "content": "<p><a href=\"/barnwellguy\">@barnwellguy</a> You are welcome</p>",
      "rawMarkdown": "barnwellguy You are welcome",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 677718,
      "author_name": "barnwellguy",
      "author_url": "",
      "post_date": "11/20/2019 14:20:15",
      "content": "<p>Thanks. Those are good reads.</p>",
      "votes": null,
      "replies": [
        {
          "id": 677769,
          "author_name": "hamditarek",
          "author_url": "",
          "post_date": "11/20/2019 15:14:34",
          "content": "<p><a href=\"/barnwellguy\">@barnwellguy</a> You are welcome</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "653840": "![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1673888%2Fd085caeab66fe5a2d9cb3d4e03ab8e57%2Fforcast.png?generation=1571628252023548&amp;alt=media)\n\nIn this discussion, I had tried to collect top solutions for the  **Google Web Traffic Time Series Forecasting : Forecast future traffic to Wikipedia pages**. This old competition present a **Time Series Forecasting** problem which may help some people to improve their solution. You can add any helpful content to help each other.\n\n[1st place solution](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43795)\n[6th-Place Solution Overview](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39370)\n[8th place with Kalman filters\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43727#latest-492742)\n[3rd place [after the first update] solution is based on kNN\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39876#latest-244632)\n[7th place solution\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43621#latest-245353)\n[Description of 5th place solution\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43603#latest-357348)\n[30th Place Approach and Lessons Learned\n](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43569#latest-244681)",
    "677718": "Thanks. Those are good reads.",
    "677769": "barnwellguy You are welcome"
  },
  "source": "meta"
}