Deep Learning and Neural Networks

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What is the term used to describe the process where a neural network adjusts each weight to minimize the difference between the computed value and the correct value?

Feed Forward Network

Forward Propagation

Hidden Layers Adjustment

Backpropagation (correct)

Which function is used to compute the difference between the desired output and the current output in a neural network?

Optimization function

Backpropagation function

Loss function (correct)

Activation function

In the context of neural networks, what does forward propagation involve?

Neurons taking input values multiplied by weights (correct)

Adjusting weights based on error

Passing error information back through the network

Calculating the loss function

What is the primary purpose of backpropagation in a neural network?

Update weights to minimize errors Signup and view all the answers

How does a neural network mimic human brain thinking?

By having more paths and connections between input and output Signup and view all the answers

Which process involves cascading input values through a neural network to affect the output?

Forward Propagation Signup and view all the answers

What is the main purpose of adjusting the weights in a neural network?

To increase the accuracy of the network's predictions Signup and view all the answers

In neural networks, what type of learning tasks do they generally perform?

Supervised learning tasks Signup and view all the answers

What type of data do neural networks interpret through machine perception?

Numerical data Signup and view all the answers

In deep learning, why is Stochastic Gradient Descent preferred over using the entire training data at once?

To speed up the learning process without degrading performance Signup and view all the answers

What allows sophisticated neural networks to identify features that may appear in different parts of the input data?

Convolution Signup and view all the answers

What is the role of a loss function in a neural network?

To minimize prediction errors Signup and view all the answers

What algorithm uses the gradient of the loss function to adjust a model's parameters during training?

Backpropagation algorithm Signup and view all the answers

In the context of deep learning, what does Gradient Descent aim to minimize?

Loss function Signup and view all the answers

Why is it mentioned that a computer can't identify the lowest point on a 3D graph by eye?

To emphasize the process of Gradient Descent Signup and view all the answers

Which term refers to the landscape exploration technique used for finding the minimum point in a convex problem like linear functions?

Gradient Descent Signup and view all the answers

What is the purpose of updating weight values using update calculations during Gradient Descent?

To minimize the 'loss' for every point in the training data Signup and view all the answers

Why is it crucial to find the best line in deep learning?

To minimize the loss for all points in training data Signup and view all the answers