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by jph00
2052 days ago
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Perhaps more relevant for this topic is the computational linear algebra course from fast.ai: https://www.fast.ai/2017/07/17/num-lin-alg/ It has a lot more detail on stuff like floating point storage, memory layout, sparse matrices, iterative methods, etc than most linear algebra courses, but doesn't go much in to proofs, geometric interpretations, and other stuff that's less needed for algorithm design and implementation. (Disclaimer, I'm from fast.ai.) |
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