Add Resource
When the user wants to add a learning resource to their repository:
Instructions
- •
Determine which topic folder the resource belongs to:
- •foundations/ - Math, statistics, algorithms, systems
- •data-analytics/ - EDA, visualization, SQL, data wrangling, business analytics
- •machine-learning/ - Traditional ML, supervised/unsupervised learning
- •deep-learning/ - Neural networks, transformers, CNNs, etc.
- •ml-system-design/ - System design for ML applications
- •ai-engineering/ - LLMs, agents, RAG, prompt engineering
- •productionization/ - MLOps, deployment, monitoring
- •software-engineering/ - Best practices, design patterns
- •ai-productivity/ - AI-powered tools (ChatGPT, Claude, Cursor, Copilot, etc.)
- •interview-prep/ - Interview-specific materials
- •
Read the current resources.md file in that folder
- •
Add the resource in consistent format:
markdown- [Title](link) - Author/Source - Brief description of what it covers
- •
Organize entries:
- •Group by type (Books, Articles, Courses, Papers, etc.) if multiple types exist
- •Within each type, maintain alphabetical order by title
- •If the file is empty, start with a simple list
Examples
Book
markdown
- [Designing Data-Intensive Applications](https://dataintensive.net/) - Martin Kleppmann - Deep dive into distributed systems, storage, and processing
Course
markdown
- [CS229: Machine Learning](https://cs229.stanford.edu/) - Stanford - Andrew Ng's classic ML course covering fundamentals
Article
markdown
- [Attention Is All You Need](https://arxiv.org/abs/1706.03762) - Vaswani et al. - Original transformer architecture paper
Edge Cases
- •If unclear which folder: Ask the user or suggest the most relevant one
- •If resource fits multiple topics: Add to primary topic and note cross-reference
- •If resources.md doesn't exist yet: Create it with proper header