Neural Networks Explained as Linear Regression for Statisticians

A new paper published on arXiv introduces neural networks to statisticians by framing them as an extension of linear regression. The authors aim to lower the barrier to entry for statisticians by explaining common customizations that build upon this foundational concept. This approach seeks to demystify neural networks for those with a classical, frequentist background. AI

RANK_REASON The cluster contains an academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

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• Neural Networks as Linear Regression: An Introduction for Statisticians

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