Cache Replacement Policies: How LRU, LFU, FIFO, MRU, and Pseudo-LRU Work in Real Systems

Beyond textbook theory: Discover how cache replacement policies like LRU, LFU, and PLRU operate across CPU caches, Linux kernel reclaim, and databases.

Beyond textbook theory: Discover how cache replacement policies like LRU, LFU, and PLRU operate across CPU caches, Linux kernel reclaim, and databases.

Ollama vs vLLM vs LM Studio: See why architecture decides cold starts, concurrency, tool calling and cost, and when to migrate. Sourced 2026 benchmarks.

Learn how SARIMA works, choose seasonal parameters, validate forecasts, and build a reproducible Python model with statsmodels.

Polars vs pandas on 10GB in 2026: verified benchmarks, why multipliers range from 3x to 94x, where DuckDB fits, memory limits, and who should stay on pandas.

Learn ARIMAX dynamic regression in Python and R: choose exogenous variables, supply future X, identify lags, check residuals, and avoid forecast leakage.

Learn ARIMA the practical way: a readiness test, working Python code, rolling validation, and a real airline-data experiment showing where models fail.

A production guide to detecting index drift and cross-tenant leaks in multitenant vector databases, with real failure cases from Milvus, Pinecone and pgvector.

Prepare for data warehouse interviews with 40+ practical questions on SQL, dimensional modeling, ETL, cloud warehouses, performance, quality, and design.

Nested loops are rarely the real problem. Learn 3 design questions that expose what your Python loops are hiding, with before/after code and Big O advice.

Build a scalable Python project structure for FastAPI: thin routers, services, Pydantic Settings, uv, Docker, and pytest overrides with real case studies.