{
  "rdb": {
    "history": [
      {
        "created_at": "2025-12-29T03:38:08",
        "id": 1,
        "metric_communication_clarity": "1.00",
        "metric_reasoning_depth": "0.00",
        "metric_technical_accuracy": "0.00",
        "question_id": "data_cleaning_98e6e04c23",
        "question_text": "What is type of your dataset?",
        "score_overall": "0.00",
        "user_answer": "That's it",
        "user_id": "test_user_025"
      },
      {
        "created_at": "2026-01-07T23:49:59",
        "id": 90001,
        "metric_communication_clarity": "1.00",
        "metric_reasoning_depth": "0.00",
        "metric_technical_accuracy": "0.00",
        "question_id": "scikit_learn_76425b6b8d",
        "question_text": "What is out of core learning?",
        "score_overall": "0.00",
        "user_answer": "First of all, I'm lo currently pursuing my core in artificial intelligence and data science.",
        "user_id": "test_user_025"
      },
      {
        "created_at": "2026-01-07T23:51:57",
        "id": 90002,
        "metric_communication_clarity": "1.00",
        "metric_reasoning_depth": "1.00",
        "metric_technical_accuracy": "1.00",
        "question_id": "algorithm_selection_c98a1d08c5",
        "question_text": "Suppose you are trying to solve a classification problem; how do you decide which algorithm to use? Give scenarios.",
        "score_overall": "1.00",
        "user_answer": "In classification from like uh, when we are classifying the breast cancer reduction be like uh bin and.",
        "user_id": "test_user_025"
      },
      {
        "created_at": "2026-01-07T23:57:23",
        "id": 90003,
        "metric_communication_clarity": "2.00",
        "metric_reasoning_depth": "3.00",
        "metric_technical_accuracy": "3.00",
        "question_id": "algorithm_selection_c98a1d08c5",
        "question_text": "Suppose you are trying to solve a classification problem; how do you decide which algorithm to use? Give scenarios.",
        "score_overall": "3.00",
        "user_answer": "When solving the Classification Pro problem, I decided to check whether the data check whether the following the data characteristics, problem complexity, integration needs and.",
        "user_id": "test_user_025"
      },
      {
        "created_at": "2026-01-08T00:02:59",
        "id": 90004,
        "metric_communication_clarity": "4.00",
        "metric_reasoning_depth": "5.00",
        "metric_technical_accuracy": "4.00",
        "question_id": "algorithm_selection_c98a1d08c5",
        "question_text": "Suppose you are trying to solve a classification problem; how do you decide which algorithm to use? Give scenarios.",
        "score_overall": "4.00",
        "user_answer": "When I solving the classification problem, I decide the problem cont contains some data characteristics, problem complexity, integrative needs and performance requirements. When considering the classification problem, we have to check the five checklist.",
        "user_id": "test_user_025"
      },
      {
        "created_at": "2026-01-08T00:06:54",
        "id": 90005,
        "metric_communication_clarity": "9.00",
        "metric_reasoning_depth": "8.00",
        "metric_technical_accuracy": "9.00",
        "question_id": "image_classification_46210c9e54",
        "question_text": "List down algorithms for segmentation",
        "score_overall": "9.00",
        "user_answer": "K-Means Clustering\n\nGroups pixels into K clusters\n\nExample: Color-based segmentation\n\nMean Shift\n\nDensity-based clustering\n\nExample: Object tracking\n\nGaussian Mixture Model (GMM)\n\nProbabilistic clustering\n\nExample: Soft segmentation\n\n\ud83d\udd39 Graph-Based Methods\n\nGraph Cut\n\nSegmentation as energy minimization\n\nExample: Foreground-background separation\n\nNormalized Cuts\n\nGraph partitioning approach\n\nExample: Complex scene segmentation\n\n\ud83d\udd39 Deep Learning-Based Methods (VERY IMPORTANT)\n\nFully Convolutional Networks (FCN)\n\nEnd-to-end pixel-wise segmentation\n\nU-Net\n\nEncoder-decoder architecture\n\nExample: Medical image segmentation\n\nSegNet\n\nEfficient encoder-decoder network\n\nDeepLab (v1\u2013v3+)\n\nUses atrous convolution\n\nExample: Semantic segmentation\n\nMask R-CNN\n\nInstance segmentation\n\nExample: Object-level masks\n\n2\ufe0f\u20e3 TEXT / NLP SEGMENTATION\n\nRule-Based Segmentation\n\nUses predefined rules\n\nExample: Sentence segmentation\n\nTopic Modeling (LDA)\n\nGroups text into topics\n\nExample: Document segmentation\n\nClustering (K-Means, Hierarchical)\n\nGroups similar text segments",
        "user_id": "test_user_025"
      }
    ],
    "profile": {
      "categories": [],
      "domain": null,
      "name": "test_user_025",
      "skills": [],
      "strengths": [],
      "thread_id": null,
      "updated_at": "2026-03-03T12:18:29",
      "user_id": "test_user_025",
      "weaknesses": []
    },
    "scores": {
      "communication_clarity": 2.94,
      "question_attempted": 6,
      "reasoning_depth": 2.89,
      "score_overall": 2.51,
      "technical_accuracy": 2.93,
      "user_id": "test_user_025"
    }
  },
  "state": {},
  "thread_id": null,
  "user_id": "test_user_025",
  "vector": {
    "id": "test_user_025",
    "metadata": {
      "domain": "unknown",
      "skills": [],
      "strengths": [
        "Technical accuracy",
        "Clear structure"
      ],
      "type": "profile_snapshot",
      "updated_at": 1767830821,
      "user_id": "test_user_025",
      "user_summary": "",
      "version": "v3",
      "weaknesses": [
        "Depth lacking"
      ]
    },
    "namespace": "profiles_v1"
  }
}