Python has become the prime language for application development in the Data Science and Machine Learning domains. However, data scientists are not necessarily experienced programmers. While Python lets them quickly implement their algorithms, when moving at scale, computation efficiency becomes inevitable. Thus, harnessing high-performance devices such as multicore processors and Graphical Processing Units (GPUs) to their potential is generally not trivial. The present narrative survey was thought as a reference document for such practitioners to help them make their way in the wealth of tools and techniques available for the Python language. Our document revolves around user scenarios, which are meant to cover most situations they may face. We believe that this document may also be of practical use to tool developers, who may use our work to identify potential lacks in existing tools and help them motivate their contributions.
翻译：Python已成为数据科学和机器学习领域应用开发的主要语言。 然而,数据科学家并不一定是有经验的程序员。 Python让他们快速地运用算法,在大规模移动时,计算效率是不可避免的。因此,利用多核心处理器和图形处理器等高性能设备发挥自身潜力一般并非微不足道。本叙述性调查被视为这些从业人员的参考文件,帮助他们掌握可供Python语言使用的大量工具和技术。我们的文件围绕用户的情景,这些情景意在涵盖他们可能面临的大多数情况。我们认为,这份文件对于工具开发者来说也可能是实用的,他们可以利用我们的工作来查明现有工具中缺乏的潜力,并帮助他们作出贡献。
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