Representation of Data: Machine learning models operate on data, which is often represented as matrices and vectors. Linear algebra provides the mathematical framework to manipulate and process this ...
[1] mml-book.github.io Copyright 2020 by Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong. To be published by Cambridge University Press. [2] Aerts, D., 1999 ...
Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data transformations. Different books cater to various needs. Some focus on ...
As data analytics has become an important application for modern data management systems, a new category of data management system has appeared recently: the scalable linear algebra system. We argue ...
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Abstract: Linear algebra algorithms are used widely in a variety of domains, e.g machine learning, numerical physics and video games graphics. For all these applications, loop-level parallelism is ...
Abstract: Approaching the post-Moore's law era, researchers are looking for scalable ways to get useful computation from existing silicon technology. This article presents a programmable analog ...
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