recall

Practical, Linux-first guide to trustworthy vector database benchmarking: bash-friendly apt/dnf/zypper setup, a reproducible harness to generate data or plug in embeddings, and measurements of recall@k, p50/p95 latency and QPS for FAISS (in-process) and Qdrant (via Podman). Match recall before comparing speed, pin CPUs, test filters/concurrency, track cost, and extend the script to other engines.

Practical, bash-first guide to AI metrics with apt/dnf/zypper installs and ready-to-run commands. Measure classifier precision/recall/F1 and confusion matrices; regression MAE/RMSE/R2; generative BLEU/ROUGE. Benchmark latency (mean, P95/P99), memory, and CPU/GPU via hyperfine, time, sysstat, nvidia-smi; compute tails from logs with jq; wire checks into CI to cut cost, catch regressions, and build trust.