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AI-Engineer-Headquarters

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

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Jupyter Notebookragagent-appllm-securityllm-inferencellmpythonpytorchaiengineeringmachine-learningdata-structures-and-algorithmsmlopsnatural-language-processingstatisticsai-agentsllm-evaluationlangchaindeep-learningailanggraph

AI-Engineer-Headquarters is a Jupyter Notebook repository that bills itself as a collection of scientific methods, processes, algorithms, and systems for building stories and models. Its topics cover machine learning, deep learning, PyTorch, NLP, statistics, MLOps, and an LLM/agentic stack including LangChain, LangGraph, RAG, LLM evaluation, inference, and security.

Reach for it when you want a single notebook-based reference spanning classic ML foundations through LLM and agent engineering practices.

Use it to

  • Study ML and deep learning fundamentals in notebooks
  • Explore LangChain and LangGraph agent patterns
  • Review RAG and LLM evaluation techniques
  • Examine LLM security and inference topics
  • Reference MLOps and statistics material

For AI and machine learning engineers learning applied LLM workflows

Role
agent-app
Language
Jupyter Notebook
Forks
699
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10
Last push
2026-09-14
topicsmachine-learningllmai-agentslangchainragmlops