Can you explain what a loss function is and how it impacts the training of machine learning models?

A loss function measures how well a machine learning model’s predictions match the actual outcomes. It calculates the error or difference between predicted and true values.

Impact on Training:

1. Guides Optimization: The loss function provides feedback that guides the optimization algorithm (like gradient descent) in adjusting model parameters to minimize errors.
2. Model Performance: A well-chosen loss function helps the model learn effectively and generalize well to new data, while a poorly chosen one can lead to suboptimal performance or slow convergence.