Study Notes

Personal notes on machine learning, data science, LLM engineering, and US tech interviews.

Interview Prep

• ML Interview Review: fundamentals → deep learning → Transformers/LLMs, a resume-driven deep dive (fraud/imbalanced learning, LoRA/quantization, MLOps, retrieval/RAG, agents, A/B testing & causal inference, recsys), and a pre-interview self-check
• Resume Questions: resume-driven deep-dive question bank, grouped by project and skill theme, for the hiring-manager round
• Leetcode Notes
• Product Sense
• Notes for AMZ

LLM

• Call OpenAI: calling the OpenAI API
• LangChain: LangChain notes for LLM apps
• AI Agent 面试 100 题: 100-question self-test bank on agents, no answers (concepts, frameworks, planning, memory, tools, RAG, evaluation)

Data Science

• Statistics Review
• SQL Review
• ML Review (v1.0 archive)
• Python for DS
• ML Pipeline for DS
• Featuretools: Automatic feature engineering

Tools

• MLflow: ML lifecycle management
• Docker for DS
• Code Engine: IBM Cloud Service for apps and jobs
• Github memo
• Tools Installation