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AI and Machine Learning: Difference between revisions
Introduction
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To get the most out of our clusters for machine learning applications, special care must be taken. A cluster is a complicated beast that is very different from your local machine that you use for prototyping. Notably, a cluster uses a distributed filesystem, linking many storage devices seamlessly. Accessing a file on <tt>/project</tt> ''feels the same'' as accessing one from the current node; but under the hood, these two IO operations have very different performance implications. In short, you need to choose wisely where to put your data. | |||
The sections below are a starting point for machine learning practitioners looking for solutions, or just getting started working with our clusters. | |||
= Python = | = Python = | ||