Books
Foundational texts covering machine learning, deep learning, statistics, reinforcement learning, and systems design.
Resources
Curated learning material, research papers, books, courses, and notes that have shaped my understanding of AI systems, machine learning, and software engineering.
This is a living collection of resources I've found valuable in my journey through AI engineering, backend systems, and applied machine learning. Each resource is chosen for its depth, clarity, and practical relevance to building production AI systems.
Categories
Research Papers
Key papers that introduced breakthrough ideas in transformers, attention mechanisms, optimization, and large language models.
GitHub Repositories
Explore a curated collection of open-source implementations, engineering patterns, and reusable Agent Skills.
The Agent Skills repository contains production-focused skills for modern AI engineering, including:
- Backend Engineering
- Frontend Development
- Data Engineering
- Agentic AI
- LLM Engineering
- DevOps & CI/CD
- System Design
- Research Paper Writing
- Software Engineering Best Practices
These skills are designed to be reusable across modern AI coding platforms such as Claude Code, OpenAI Codex, Gemini CLI, Cursor, Windsurf, Cline, Roo Code, GitHub Copilot, and other agentic development environments. They can also be integrated as plugins or customized to support production AI workflows.
Courses & Lectures
University courses, online lectures, and tutorials from leading institutions and practitioners.
Blogs & Technical Writing
Engineering blogs, deep dives, and technical posts that explain complex systems clearly.
Talks & Presentations
Conference talks, technical presentations, and recorded discussions on AI systems and engineering.
Notes & References
Personal notes, summaries, and quick references for algorithms, architectures, and design patterns.
Coming Soon: Detailed resource listings with annotations, categories, difficulty levels, and recommendations for different learning paths.