Learn from top Kaggle solutions across text, images, time series, tabular data, and multimodal tasks that combine data types. Explore technical analyses, model settings, reusable code templates, and practical lessons to inform machine learning projects.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Extract and apply knowledge from Kaggle competition winning solutions. This skill provides access to a continuously updated knowledge base of techniques, code patterns, and best practices from top Kaggle competitors.
Kaggle competitions are at the forefront of practical machine learning. Winning solutions often innovate with novel techniques, clever feature engineering, and optimized pipelines. This skill captures that knowledge and makes it accessible for your projects.
Use this skill when:
| Category | Focus | Directory |
|---|---|---|
| NLP | Text classification, NER, translation, LLM applications | references/knowledge/nlp/ |
| CV | Image classification, detection, segmentation, generation | references/knowledge/cv/ |
| Time Series | Forecasting, anomaly detection, sequence modeling | references/knowledge/time-series/ |
| Tabular | Feature engineering, traditional ML, structured data | references/knowledge/tabular/ |
| Multimodal | Cross-modal tasks, vision-language models | references/knowledge/multimodal/ |
文件组织结构：每个竞赛一个独立的 markdown 文件，按 domain 分类到对应目录。
示例：
time-series/birdclef-plus-2025.mdnlp/aimo-2-2025.mdTo learn from a competition:
To browse existing knowledge:
references/knowledge/[domain]/This skill automatically updates its knowledge base when the kaggle-miner agent processes new competitions. The more you use it, the smarter it becomes.
每次从 Kaggle 竞赛提取知识时，必须包含以下标准部分：
| 部分 | 说明 | 必需性 |
|---|---|---|
| Competition Brief | 竞赛背景、任务描述、数据规模、评估指标 | ✅ 必需 |
| Original Summaries | 前排方案的简要概述 | ✅ 必需 |
| 前排方案详细技术分析 | Top 20 方案的核心技巧和实现细节 | ✅ 必需 ⭐ |
| Code Templates | 可复用的代码模板 | ✅ 必需 |
| Best Practices | 最佳实践和常见陷阱 | ✅ 必需 |
| Metadata | 数据源标签和日期 | ✅ 必需 |
每个前排方案应包含：
示例格式：
**排名 Place - 核心技术名称 (作者)**
核心技巧：
- **技巧1**: 简短说明
- **技巧2**: 简短说明
实现细节：
- 具体参数、模型、配置
- 数据和实验结果
建议覆盖 Top 20 方案，获取更多前排选手的创新技巧
references/knowledge/nlp/ - NLP competition techniquesreferences/knowledge/cv/ - Computer vision techniquesreferences/knowledge/time-series/ - Time series methodsreferences/knowledge/tabular/ - Tabular data approachesreferences/knowledge/multimodal/ - Multimodal solutionstime-series/birdclef-plus-2025.md) - 包含完整的 Top 14 前排方案详细技术分析time-series/birdclef-2024.md) - 包含 Top 3 方案详细技术分析nlp/aimo-2-2025.md) - 包含 Top 12+ 前排方案技术总结아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Turn a broad research idea into clear, testable questions. Compare familiar and less conventional approaches, structure the selected question around its population and methods, and assess variables, feasibility, and potential theoretical contributions.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Helps build a research framework by comparing theories, mapping relationships between variables, and deriving testable hypotheses. Explores less conventional options, examines weaknesses and competing explanations, and produces diagrams with anticipated reviewer objections.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Clarify the philosophical assumptions behind a research project and check whether they fit the proposed methods. Get a reasoned research stance, draft proposal wording, and guidance for explaining how the researcher's background and values shape the study.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Plan and draft academic papers through specialized agent roles covering literature, arguments, citations, and review. Get chapter guidance, revision roadmaps, Traditional Chinese and English abstracts, and documents formatted as LaTeX, DOCX, PDF, or Markdown.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn a detailed outline into a philosophy or interdisciplinary manuscript. Draft chapters with repeated quality reviews, check terminology and arguments across sections, and prepare the manuscript, evaluation reports, abstract, and metadata for submission.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Simulate academic peer review through five reviewer roles tailored to the paper's field. Receive separate critiques, an editorial decision, and a prioritized revision roadmap, or check whether a revised manuscript addresses earlier comments.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.