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Guide to building clean, reproducible, GPU‑aware AI environments on Linux from the shell: install minimal system prerequisites; create isolated envs with Python venv or micromamba; pick and install correct PyTorch/TensorFlow CPU, CUDA, or ROCm wheels; verify GPU; pin/lock and cache dependencies for offline/CI; export conda envs; run a quick MNIST example; add a Bash helper; avoid sudo pip and mixing managers; next step: containerize for CI.