159 PDFs covering generative AI, software engineering, cloud platforms, certifications, and interview prep.
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INDEX.md
| # | Directory | What's inside |
|---|---|---|
| 1 | 01_programming/ |
Python, SQL, TypeScript, React, FastAPI, API design |
| 2 | 02_development_tools/ |
Git, Docker, VS Code, Markdown |
| 3 | 03_generative_ai/ |
The main section — see breakdown below |
| 4 | 04_presentations/ |
Slide decks: BI, cybersecurity, data science, fintech, keynotes |
| 5 | 05_certifications/ |
AWS and GitHub certification exam guides |
| 6 | 06_interview_prep/ |
Interview tips and LLM Q&A |
| Subdirectory | Focus |
|---|---|
agents/ |
Agent design, evaluation, and production guides |
anthropic/ |
Claude and Claude Code best practices |
aws/ |
Bedrock, GenAI on AWS, whitepapers |
deeplearning/ |
ML fundamentals, PyTorch, deep learning |
google/ |
Vertex AI, prompting guides, Gemini |
guides_and_books/ |
General GenAI playbooks and roadmaps |
langchain/ |
LangChain, LangGraph, agent frameworks |
llm_fundamentals/ |
Embeddings, chunking, caching, fine-tuning, context engineering |
neo4j/ |
Graph databases and GraphRAG |
nvidia/ |
Inference servers and agentic AI development |
openai/ |
GPT guides, Codex, enterprise AI |
papers/ |
Attention, FlashAttention, ReAct, RAG, and more |
prompting/ |
Prompt engineering guides and playbooks |
rag/ |
RAG architectures, types, and pipeline optimization |
- Drop it in the right subdirectory
- Push to a new branch and open a pull request
- Once merged to
main, CI auto-renames it to a clean snake_case name using AI and regenerates the index - No API keys needed; everything runs on the built-in
GITHUB_TOKEN