Personal notes on machine learning, data science, LLM engineering, and US tech interviews.
- 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
- Leetcode Notes
- Product Sense
- Notes for AMZ
- Call OpenAI: calling the OpenAI API
- LangChain: LangChain notes for LLM apps
- Statistics Review
- SQL Review
- ML Review (v1.0 archive)
- Python for DS
- ML Pipeline for DS
- Featuretools: Automatic feature engineering
- MLflow: ML lifecycle management
- Docker for DS
- Code Engine: IBM Cloud Service for apps and jobs
- Github memo
- Tools Installation