![]() ![]() The benefits of Ubuntu are clear, however, not all data scientists use Ubuntu machines. Running Ubuntu directly on Windows with WSL 2 ![]() NVIDIA GPUs are critical for complex AI/ML workloads, and Linux enables users to take full advantage of NVIDIA CUDA to achieve more granular control over the hardware than is possible with Windows. The final piece of the puzzle is GPU acceleration. Since it is at home on workstations, bare-metal, in the cloud, and at the edge, Ubuntu offers a seamless path from development to testing to production all on the same operating system with the same tools, unlocking a host of efficiencies. This enables Ubuntu users to easily take advantage of existing guidance and code, making data science more accessible on Ubuntu than on any other platform.Īdditionally, Ubuntu allows users to develop where they deploy. Likewise, the majority of artificial intelligence and machine learning documentation is written with Ubuntu in mind. Not only does Ubuntu offer one of the broadest and best-supported libraries of key data science tools, but many of these tools are also developed with Ubuntu as their target platform. ![]() Given the platform’s popularity, especially among developers, it is no surprise that Ubuntu has become the industry standard operating system for data science workflows, used by the likes of Netflix, Tesla, OpenAI, and countless others. Ubuntu is the most widely used Linux distribution globally, and the leading operating system across all major public clouds. In addition to native Ubuntu offerings, select Z by HP workstations are also available with Windows Subsystem for Linux 2 (WSL 2) pre-installed and pre-enabled, giving users the ability to accelerate data science workflows on Ubuntu straight out of the box, without leaving their native Windows OS. ![]()
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