Add Resource

When the user wants to add a learning resource to their repository:

Instructions

1. 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

2. Read the current resources.md file in that folder

3. Add the resource in consistent format:

   markdownCopy

   - [Title](link) - Author/Source - Brief description of what it covers
   

4. 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

- [Designing Data-Intensive Applications](https://dataintensive.net/) - Martin Kleppmann - Deep dive into distributed systems, storage, and processing

Course

- [CS229: Machine Learning](https://cs229.stanford.edu/) - Stanford - Andrew Ng's classic ML course covering fundamentals

Article

- [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