kaggle-learnerlisted

# Kaggle Learner 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. ## Overview 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. ## When to Use Use this skill when: - Studying for a Kaggle competition - Looking for proven techniques in a specific domain (NLP, CV, etc.) - Need code templates for common ML tasks - Want to learn from competition winners ## Knowledge Categories | 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/` | **File组织结构**：每个竞赛一个独立的 markdown File，按 domain 分Class到对应Directory。 Example： - `time-series/birdclef-plus-2025.md` - `nlp/aimo-2-2025.md` ## Quick Reference