Neural Network Basics
What does it mean to train a neural network?
Teaching it to make better predictions
What is the last step in the training process?
Updating the weights
Which loss function is used for regression problems?
Mean Squared Error (MSE)
Which PyTorch module is used to define a loss function?
torch.nn
What does an optimizer help with in neural networks?
Reducing the loss by updating weights
What is the main purpose of epochs in training a neural network?
To define the number of training iterations
What does zero_grad() do in the training loop?
Resets the gradients before the backward pass
Which optimizer is known to be simple but slow?
SGD
What does model.eval() do in PyTorch?
Sets the model to evaluation mode
What is a forward pass?
The process of making a prediction using the model
What does the backward pass in a neural network do?
Calculates gradients
What does the optimizer do in training a neural network?
Updates model parameters to reduce loss
Which optimizer is widely used for deep learning?
Adam
How do we save a PyTorch model?
torch.save(model, "model.pth")
What does it mean when a model "overfits"?
It performs well on training data but poorly on new data
What is the purpose of testing a trained model?
To see how well it performs on new data
Which step is NOT part of training a neural network?
Deleting the model after training
What happens if the learning rate is too high?
The model fails to learn properly
Which function loads a saved PyTorch model?
torch.load()
What is gradient descent used for?
Minimizing the loss function
What is the first step in training a neural network?
Making a prediction (forward pass)
What is the purpose of the loss function in a neural network?
To measure how wrong the prediction is
What is the purpose of a loss function?
To measure how wrong the prediction is
Which PyTorch module is used to define a neural network model?
torch.nn
Why do we use validation data during training?
To monitor the model’s performance on unseen data