🔬Research
📖
Reading ML Papers
Develop the skill of efficiently reading and understanding machine learning research papers
🌱
Beginner
BeginnerGetting started with papers
What to Learn
- •Paper structure (abstract, intro, methods, experiments)
- •Finding relevant papers (arXiv, Semantic Scholar)
- •Reading strategies: first, second, third pass
- •Understanding common notation
- •Starting with survey papers
Resources
- 📚How to Read a Paper (Keshav)
- 📚arXiv Sanity Preserver
- 📚Papers With Code
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Intermediate
IntermediateDeep paper comprehension
What to Learn
- •Reproducing paper experiments
- •Critical analysis of claims
- •Understanding ablation studies
- •Connecting papers to broader literature
- •Reading math-heavy papers
Resources
- 📚Paper reading groups online
- 📚ML Reproducibility Challenge
- 📚The Morning Paper (blog)
🌳
Advanced
AdvancedResearch-level understanding
What to Learn
- •Identifying research gaps
- •Evaluating novelty and contribution
- •Building mental models of research areas
- •Writing literature reviews
- •Staying current with the field
Resources
- 📚How to write a good paper (MLSS)
- 📚Research methodology courses
- 📚Conference reviewing guidelines