A recipe for training neural networks

Abstract

Neural network training requires an understanding of both the algorithm and the data. Training often fails silently, even if all code is correct. A carefully planned, step-by-step process can help identify and resolve these issues. Steps involve becoming familiar with the data, establishing a training and evaluation framework, fitting to the data, regularizing the model, fine tuning, and squeezing out the juice. – AI-generated abstract.