{
  "id": 337274,
  "title": "New way to monitor and experiment-tracking",
  "url": "/competitions/amex-default-prediction/discussion/337274",
  "author_name": "",
  "post_date": "2022-07-15T08:55:00.331561600Z",
  "votes": 2,
  "comment_count": 3,
  "views": 0,
  "content": "<p>Hey!</p>\n<p>I came across <a href=\"https://www.truefoundry.com\" target=\"_blank\">TrueFoundry</a>, which is currently working on a problem in the Machine Learning domain wherein they want to make model sharing and deployment easier. TrueFoundry gives Data Scientists and ML Engineers the fastest framework for Post model Pipelines. We enable instantly monitored endpoints for models in 15 minutes with the best DevOps practices. I've seen some Kagglers already using it and thought to share it with everyone here in the competition since it can be of great help.</p>",
  "messages": [
    {
      "id": "1856308",
      "postDate": "07/15/2022 08:55:00",
      "content": "<p>Hey!</p>\n<p>I came across <a href=\"https://www.truefoundry.com\" target=\"_blank\">TrueFoundry</a>, which is currently working on a problem in the Machine Learning domain wherein they want to make model sharing and deployment easier. TrueFoundry gives Data Scientists and ML Engineers the fastest framework for Post model Pipelines. We enable instantly monitored endpoints for models in 15 minutes with the best DevOps practices. I've seen some Kagglers already using it and thought to share it with everyone here in the competition since it can be of great help.</p>",
      "rawMarkdown": "Hey!\n\nI came across [TrueFoundry](https://www.truefoundry.com), which is currently working on a problem in the Machine Learning domain wherein they want to make model sharing and deployment easier. TrueFoundry gives Data Scientists and ML Engineers the fastest framework for Post model Pipelines. We enable instantly monitored endpoints for models in 15 minutes with the best DevOps practices. I've seen some Kagglers already using it and thought to share it with everyone here in the competition since it can be of great help.",
      "votes": null
    },
    {
      "id": "1857148",
      "postDate": "07/15/2022 22:10:32",
      "content": "<p>Hello <a href=\"https://www.kaggle.com/gargmanas\" target=\"_blank\">@gargmanas</a>, I will look at some point; I have been using Neptune.AI for quite some time. So will this what this one can offer.</p>",
      "rawMarkdown": "Hello @gargmanas, I will look at some point; I have been using Neptune.AI for quite some time. So will this what this one can offer.",
      "votes": null
    },
    {
      "id": "1858631",
      "postDate": "07/17/2022 04:55:06",
      "content": "<p>Hey <a href=\"https://www.kaggle.com/cv13j0\" target=\"_blank\">@cv13j0</a>. I personally found this pretty interesting as well. You can also deploy models super quickly and it has integrated monitoring and experiment tracking to make it a complete post-model package.</p>",
      "rawMarkdown": "Hey @cv13j0. I personally found this pretty interesting as well. You can also deploy models super quickly and it has integrated monitoring and experiment tracking to make it a complete post-model package.",
      "votes": null
    },
    {
      "id": "1862828",
      "postDate": "07/20/2022 03:32:07",
      "content": "<p>Thanks <a href=\"https://www.kaggle.com/gargmanas\" target=\"_blank\">@gargmanas</a> the deploy capabilities look interesting, I will give it a try in the near feature, thanks again for sharing</p>",
      "rawMarkdown": "Thanks @gargmanas the deploy capabilities look interesting, I will give it a try in the near feature, thanks again for sharing",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1857148,
      "author_name": "cv13j0",
      "author_url": "",
      "post_date": "07/15/2022 22:10:32",
      "content": "<p>Hello <a href=\"https://www.kaggle.com/gargmanas\" target=\"_blank\">@gargmanas</a>, I will look at some point; I have been using Neptune.AI for quite some time. So will this what this one can offer.</p>",
      "votes": null,
      "replies": [
        {
          "id": 1858631,
          "author_name": "gargmanas",
          "author_url": "",
          "post_date": "07/17/2022 04:55:06",
          "content": "<p>Hey <a href=\"https://www.kaggle.com/cv13j0\" target=\"_blank\">@cv13j0</a>. I personally found this pretty interesting as well. You can also deploy models super quickly and it has integrated monitoring and experiment tracking to make it a complete post-model package.</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 1862828,
          "author_name": "cv13j0",
          "author_url": "",
          "post_date": "07/20/2022 03:32:07",
          "content": "<p>Thanks <a href=\"https://www.kaggle.com/gargmanas\" target=\"_blank\">@gargmanas</a> the deploy capabilities look interesting, I will give it a try in the near feature, thanks again for sharing</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "1856308": "Hey!\n\nI came across [TrueFoundry](https://www.truefoundry.com), which is currently working on a problem in the Machine Learning domain wherein they want to make model sharing and deployment easier. TrueFoundry gives Data Scientists and ML Engineers the fastest framework for Post model Pipelines. We enable instantly monitored endpoints for models in 15 minutes with the best DevOps practices. I've seen some Kagglers already using it and thought to share it with everyone here in the competition since it can be of great help.",
    "1857148": "Hello @gargmanas, I will look at some point; I have been using Neptune.AI for quite some time. So will this what this one can offer.",
    "1858631": "Hey @cv13j0. I personally found this pretty interesting as well. You can also deploy models super quickly and it has integrated monitoring and experiment tracking to make it a complete post-model package.",
    "1862828": "Thanks @gargmanas the deploy capabilities look interesting, I will give it a try in the near feature, thanks again for sharing"
  },
  "source": "meta"
}