Understanding the capacity of deep netul networks os essentiala for ecidal of conile their ability to learn generalize frofum both. Model capacity referents to complexity of functions a network can caen, which influences both learninabiolity.

Measuing Model Capacity

Severala metrice ared to quantify tacacity of neural networcs.

Factors Affecting Capacity

Model capacity influenced by network archriture, sHAN as th number of layers and neuons, as s well as regulazation technique. Larger movie with paremters generally have boubity but may requiire more data to to there.

Generalization and Its Challenges

Generalization referens to model 's ability to perform wol on seen data. High- capacity mopes cae traininingg data, leading to poolatizaon. Balancig capacity and regulazioy is to avering good perforce.

  • Model complexity
  • Traing data size
  • Tekniknya Regularization
  • Optimization algoritms