Week 8 retrospective of Naver Boostcamp AI Tech covering NLP lectures, MLOps tooling research, and validation set distribution discussions.

Introduction to quantitative trading strategies including arbitrage, market making, and statistical arbitrage.

Practical tips for Kaggle competitions covering ranking systems, competition types, validation strategies, ensemble methods, and hardware recommendations.

End-to-end process of deploying AI models as services, from requirements analysis and dataset construction to modeling, testing, and team organization.

Curated list of MLOps tools and frameworks including Wandb, Hydra, DVC, ONNX, and CI/CD options for ML project workflows.

Clarifying commonly confused NLP concepts: argmax vs. multinomial sampling, beam search vs. sampling, and Pre-LN vs. Post-LN in GPT and Transformer.