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This and fully integrated software stack is built around TensorFlow, an open-source machine learning library, and the Python programming language. It offers a stable and thoroughly tested execution environment suitable for various machine learning tasks, including training, inference, and serving as an API service.

One of its standout features is its ease of integration into continuous integration and deployment workflows, simplifying the development and deployment of machine learning applications. This stack is optimized for high-performance computing, making it suitable for both short and long-running tasks. Notably, it’s fine-tuned for NVidia GPU utilization.

The stack includes essential components such as CUDA, a parallel computing platform and API model, and cuDNN, a GPU-accelerated library designed for deep neural networks. Additionally, it comes with NVidia drivers and a Development preset, offering a comprehensive set of program development and building tools, including a C compiler and make. These tools empower users to customize and extend the environment to meet their specific machine learning needs, making it a versatile choice for developers and data scientists who want to leverage GPU acceleration for their work.