Neural Networks as Linear Regression: An Introduction for Statisticians
2026-06-22 • Machine Learning
Machine Learning
AI summaryⓘ
The authors explain neural networks in a simple way for people familiar with traditional statistics. They show how neural networks can mimic something basic like linear regression. The letter also covers common changes you can make to these networks to help understand them better. This provides a good starting point for learning more about neural networks.
neural networkslinear regressionfrequentist statisticspredictionmodel approximationcustomizationmachine learning basicsstatistical modeling
Authors
Abigail Loe, Susan Murray, Zhenke Wu
Abstract
Neural networks are a commonly used prediction tool in computer science and statistics. However, the barrier to entry of this interesting field remains high, particularly for classical statisticians trained in a frequentist perspective. In this letter, we demystify neural networks by describing networks that approximate a linear regression and describe common customizations that provide a foundation for further study.