Deep Learning and Neural Networks
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Questions and Answers

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?

    <p>Update weights to minimize errors</p> Signup and view all the answers

    How does a neural network mimic human brain thinking?

    <p>By having more paths and connections between input and output</p> Signup and view all the answers

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

    <p>Forward Propagation</p> Signup and view all the answers

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

    <p>To increase the accuracy of the network's predictions</p> Signup and view all the answers

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

    <p>Supervised learning tasks</p> Signup and view all the answers

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

    <p>Numerical data</p> Signup and view all the answers

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

    <p>To speed up the learning process without degrading performance</p> Signup and view all the answers

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

    <p>Convolution</p> Signup and view all the answers

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

    <p>To minimize prediction errors</p> Signup and view all the answers

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

    <p>Backpropagation algorithm</p> Signup and view all the answers

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

    <p>Loss function</p> 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?

    <p>To emphasize the process of Gradient Descent</p> 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?

    <p>Gradient Descent</p> Signup and view all the answers

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

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

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

    <p>To minimize the loss for all points in training data</p> Signup and view all the answers

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