Definition

Model training is the process of feeding data into a machine learning algorithm to learn patterns and relationships, adjusting the model’s parameters until it achieves a desired level of performance.

Why it matters (in Poovi’s context)

This is the most computationally demanding part of ML/AI development and directly influences the need for powerful hardware like GPUs and substantial memory, as discussed for Agnes’s requirements.

Key properties or components

  • Learning from data
  • Parameter adjustment
  • Performance optimisation
  • Computationally intensive

Contradictions or debates

None.

Sources