: Ensure you have updated DirectX and VC++ Redistributables, as many niche Japanese-developed AI apps rely on these for rendering.
# 2️⃣ Install core ML libraries (CPU‑only for now) pip install --upgrade pip pip install numpy pandas matplotlib scikit-learn pc android ochinpo learning ai onasapo premie exclusive
| Tool | Command (Ubuntu/WSL) | Windows/macOS notes | |------|----------------------|---------------------| | | sudo apt install git | Install via Git for Windows or Homebrew ( brew install git ). | | Python 3.11 | sudo apt install python3.11 python3-pip python3-venv | Windows: use the official installer; macOS: brew install python@3.11 . | | Node.js (optional for some web‑AI demos) | curl -fsSL https://deb.nodesource.com/setup_20.x \| sudo -E bash - && sudo apt install -y nodejs | Use the .pkg installer on macOS, or Chocolatey on Windows. | | Docker (for containerised training) | Follow Docker’s official script: curl -fsSL https://get.docker.com | sh | Install Docker Desktop. | | GPU driver + CUDA (if you have NVIDIA) | sudo apt install nvidia-driver-525 then install CUDA Toolkit from NVIDIA site | On Windows, install the CUDA Toolkit and cuDNN via the NVIDIA installer. | | Conda (miniforge) – optional but simplifies environment management | wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh && bash Miniforge3-Linux-x86_64.sh | Use Miniforge‑MacOS‑arm64.sh on Apple silicon. | : Ensure you have updated DirectX and VC++