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A practical, bash-first guide to reproducible, fast AI on Linux: baseline your distro (apt/dnf/zypper), use venvs for Python and containers for full stacks (esp. GPU), monitor and tune resources (htop, iostat, OMP threads, NUMA, cgroups), streamline data (Git LFS, aria2, rsync, caches), run the ready-made snippets, avoid common pitfalls, and make work trivially shareable and repeatable.