{
  "id": 722428,
  "title": "Pushing MLOps Boundaries: Hybrid GNN + HistGradientBoosting Pipeline",
  "url": "/competitions/predict-ai-model-runtime/discussion/722428",
  "author_name": "Islam Ashraf",
  "post_date": "2026-07-06T19:44:17.532000",
  "votes": 0,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Hi all, I've built an end-to-end MLOps pipeline combining Graph Neural Networks (GNNs) with HistGradientBoosting to leverage both structured relationships and tabular efficiency simultaneously. It includes full dataset tracking, robustness checks, and deployment-ready modularity.</p>\n<p>If you are into graph modeling and structured MLOps, take a look: [<a href=\"https://www.kaggle.com/code/ashrafsalahedlin/mlops-pipeline-hybrid-gnn-histgradientboosting\" target=\"_blank\">https://www.kaggle.com/code/ashrafsalahedlin/mlops-pipeline-hybrid-gnn-histgradientboosting</a>]</p>",
  "messages": [
    {
      "id": 3491894,
      "postDate": "2026-07-06T19:44:17.533Z",
      "content": "<p>Hi all, I've built an end-to-end MLOps pipeline combining Graph Neural Networks (GNNs) with HistGradientBoosting to leverage both structured relationships and tabular efficiency simultaneously. It includes full dataset tracking, robustness checks, and deployment-ready modularity.</p>\n<p>If you are into graph modeling and structured MLOps, take a look: [<a href=\"https://www.kaggle.com/code/ashrafsalahedlin/mlops-pipeline-hybrid-gnn-histgradientboosting\" target=\"_blank\">https://www.kaggle.com/code/ashrafsalahedlin/mlops-pipeline-hybrid-gnn-histgradientboosting</a>]</p>",
      "rawMarkdown": "Hi all, I've built an end-to-end MLOps pipeline combining Graph Neural Networks (GNNs) with HistGradientBoosting to leverage both structured relationships and tabular efficiency simultaneously. It includes full dataset tracking, robustness checks, and deployment-ready modularity.\n\nIf you are into graph modeling and structured MLOps, take a look: [https://www.kaggle.com/code/ashrafsalahedlin/mlops-pipeline-hybrid-gnn-histgradientboosting]"
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "3491894": "Hi all, I've built an end-to-end MLOps pipeline combining Graph Neural Networks (GNNs) with HistGradientBoosting to leverage both structured relationships and tabular efficiency simultaneously. It includes full dataset tracking, robustness checks, and deployment-ready modularity.\n\nIf you are into graph modeling and structured MLOps, take a look: [https://www.kaggle.com/code/ashrafsalahedlin/mlops-pipeline-hybrid-gnn-histgradientboosting]"
  }
}