ML 26: The Network That Memorises Noise Learns the Signal First
Disclosure: this post was written with the assistance of an AI system (Claude), which wrote the analysis code, ran the experiments and drafted the text. The topic, the constraints, the data choices and the final review are the author’s. A two-layer network with 512 units per layer, trained full-batch on 898 digits, reached 100% training accuracy in 41 steps on the true labels (test accuracy 0.968) and in 73 on entirely random labels (test 0....