What is the process called that involves adjusting the network's parameters during learning?

What is the process called that involves adjusting the network's parameters during learning?

• A. Inference
• B. Training a neural network
• C. Validation
• D. Testing

Answer: (B)

The concept being tested is the phase where a neural network learns by changing its internal settings. This is training a neural network. During training, the model processes data, calculates how far its predictions are from the true values, and then uses methods like backpropagation and gradient descent to adjust the weights and biases to reduce that error. This updating of parameters as learning progresses is what distinguishes training from other stages. Inference uses the already learned parameters to make predictions on new data, without changing them. Validation checks performance on separate data to tune settings but typically without altering the learned parameters in the primary training loop. Testing assesses final performance on unseen data after training is complete.

The concept being tested is the phase where a neural network learns by changing its internal settings. This is training a neural network. During training, the model processes data, calculates how far its predictions are from the true values, and then uses methods like backpropagation and gradient descent to adjust the weights and biases to reduce that error. This updating of parameters as learning progresses is what distinguishes training from other stages. Inference uses the already learned parameters to make predictions on new data, without changing them. Validation checks performance on separate data to tune settings but typically without altering the learned parameters in the primary training loop. Testing assesses final performance on unseen data after training is complete.