{
  "id": 295690,
  "title": "Quant-ML Resource Website",
  "url": "/competitions/g-research-crypto-forecasting/discussion/295690",
  "author_name": "",
  "post_date": "2021-12-17T09:37:14.007169300Z",
  "votes": 8,
  "comment_count": 2,
  "views": 0,
  "content": "<p>I wanted an easy way to get a pulse on hundreds of Quant research insights produced every day. The dashboard helps me check Twitter, LinkedIn, ArXiv, GitHub, Journals and hundreds of blogs every day.</p>\n<p><a href=\"https://www.ml-quant.com/\" target=\"_blank\">https://www.ml-quant.com/</a></p>\n<p>After attempting multiple solutions over the last few years, I came up with the following tech stack Notion API, GCP Function, Cloud Scheduler, and Python scrapers, and RSS feeds to develop a Quant research dashboard.</p>\n<p><img src=\"https://raw.githubusercontent.com/firmai/random-assets-two/master/assets/ml-quant.PNG\" alt=\"\"></p>",
  "messages": [
    {
      "id": "1620960",
      "postDate": "12/17/2021 09:37:14",
      "content": "<p>I wanted an easy way to get a pulse on hundreds of Quant research insights produced every day. The dashboard helps me check Twitter, LinkedIn, ArXiv, GitHub, Journals and hundreds of blogs every day.</p>\n<p><a href=\"https://www.ml-quant.com/\" target=\"_blank\">https://www.ml-quant.com/</a></p>\n<p>After attempting multiple solutions over the last few years, I came up with the following tech stack Notion API, GCP Function, Cloud Scheduler, and Python scrapers, and RSS feeds to develop a Quant research dashboard.</p>\n<p><img src=\"https://raw.githubusercontent.com/firmai/random-assets-two/master/assets/ml-quant.PNG\" alt=\"\"></p>",
      "rawMarkdown": "I wanted an easy way to get a pulse on hundreds of Quant research insights produced every day. The dashboard helps me check Twitter, LinkedIn, ArXiv, GitHub, Journals and hundreds of blogs every day.\n\nhttps://www.ml-quant.com/\n\nAfter attempting multiple solutions over the last few years, I came up with the following tech stack Notion API, GCP Function, Cloud Scheduler, and Python scrapers, and RSS feeds to develop a Quant research dashboard.\n\n![](https://raw.githubusercontent.com/firmai/random-assets-two/master/assets/ml-quant.PNG)",
      "votes": null
    },
    {
      "id": "1621032",
      "postDate": "12/17/2021 11:31:51",
      "content": "<p>Incredible stuff. I haven't finished going trough all of it (and waiting to see what the email looks like) but this looks very usefull. </p>\n<p>Some early usage toughts:</p>\n<ul>\n<li>A generic subcategory filter (Equity / rate / FX / Crypto) might be usefull</li>\n<li>A 'Data' category might be usefull</li>\n</ul>",
      "rawMarkdown": "Incredible stuff. I haven't finished going trough all of it (and waiting to see what the email looks like) but this looks very usefull. \n\nSome early usage toughts:\n- A generic subcategory filter (Equity / rate / FX / Crypto) might be usefull\n- A 'Data' category might be usefull",
      "votes": null
    },
    {
      "id": "1650526",
      "postDate": "01/15/2022 05:14:05",
      "content": "<p>This looks useful, I'll look into it later, thanks! </p>",
      "rawMarkdown": "This looks useful, I'll look into it later, thanks!",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1621032,
      "author_name": "lucasmorin",
      "author_url": "",
      "post_date": "12/17/2021 11:31:51",
      "content": "<p>Incredible stuff. I haven't finished going trough all of it (and waiting to see what the email looks like) but this looks very usefull. </p>\n<p>Some early usage toughts:</p>\n<ul>\n<li>A generic subcategory filter (Equity / rate / FX / Crypto) might be usefull</li>\n<li>A 'Data' category might be usefull</li>\n</ul>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1650526,
      "author_name": "",
      "author_url": "",
      "post_date": "01/15/2022 05:14:05",
      "content": "<p>This looks useful, I'll look into it later, thanks! </p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1620960": "I wanted an easy way to get a pulse on hundreds of Quant research insights produced every day. The dashboard helps me check Twitter, LinkedIn, ArXiv, GitHub, Journals and hundreds of blogs every day.\n\nhttps://www.ml-quant.com/\n\nAfter attempting multiple solutions over the last few years, I came up with the following tech stack Notion API, GCP Function, Cloud Scheduler, and Python scrapers, and RSS feeds to develop a Quant research dashboard.\n\n![](https://raw.githubusercontent.com/firmai/random-assets-two/master/assets/ml-quant.PNG)",
    "1621032": "Incredible stuff. I haven't finished going trough all of it (and waiting to see what the email looks like) but this looks very usefull. \n\nSome early usage toughts:\n- A generic subcategory filter (Equity / rate / FX / Crypto) might be usefull\n- A 'Data' category might be usefull",
    "1650526": "This looks useful, I'll look into it later, thanks!"
  },
  "source": "meta"
}