Artificial Intelligence Deep Learning Deep Learning Quiz Quiz Deep Learning Basics Quiz 3 Data AI Admin October 9, 2024 Welcome to the Deep Learning Basics Quiz 3! 💡In this quiz, you’ll explore advanced deep learning topics like the vanishing gradient problem, transfer learning, dropout, and GANs. Keep learning and enjoy! ⏰ Time's Up!The quiz is over, and your answers have been submitted automatically. Let’s review your knowledge of deep learning concepts! Deep Learning Basics Quiz 3 This is the third quiz in the Deep Learning Basics series, covering 10 questions on more advanced topics such as batch normalization, weight initialization, and transfer learning. Each question is designed to deepen your understanding, and some may have more than one correct answer. 1 / 10 In a neural network, what is the purpose of the weight initialization technique? To speed up convergence during training To prevent vanishing or exploding gradients To ensure accurate predictions from the start To reduce the size of the model 2 / 10 What is the vanishing gradient problem in deep learning? A problem only occurring in output layers A type of model underfitting issue A problem where gradients become too large during backpropagation A problem where gradients become too small during backpropagation 3 / 10 What does batch normalization do in a neural network? It reduces overfitting by adding regularization It increases the number of neurons in a hidden layer It normalizes the activations of the previous layer in a mini-batch It normalizes the input data before feeding it into the network 4 / 10 What is the primary purpose of the ReLU activation function in neural networks? To prevent overfitting To reduce the size of the network To introduce non-linearity to the network To scale input values between 0 and 1 5 / 10 What is transfer learning in deep learning? Transferring data from one model to another Using a pre-trained model and adapting it for a new task Training a model from scratch on a new dataset Sharing parameters between two models 6 / 10 Which of the following models is primarily used for sequential data? Convolutional Neural Networks (CNN) Recurrent Neural Networks (RNN) Feedforward Neural Networks Generative Adversarial Networks (GAN) 7 / 10 What is a dropout layer in deep learning? A layer that drops input features A layer that removes noisy data from the input A layer that randomly drops neurons during training to prevent overfitting A layer used to reduce dimensionality of data 8 / 10 Which of the following activation functions can help address the vanishing gradient problem? Leaky ReLU Tanh Sigmoid ReLU 9 / 10 Which deep learning model is most commonly used for generating new data, like images or text? Convolutional Neural Networks (CNN) Generative Adversarial Networks (GAN) Multilayer Perceptrons (MLP) Recurrent Neural Networks (RNN) 10 / 10 Which of the following is an unsupervised learning technique used in deep learning? Autoencoders Decision Trees K-means clustering Support Vector Machines Your score isThe average score is 0% 0% Restart quiz Share this… Whatsapp Linkedin Facebook Twitter Gmail Related Tags: Deep Learning, Deep Learning Quiz, Quiz Continue Reading Previous Deep Learning Basics Quiz 2Next Data Science Expert Quiz 10 More Stories Natural Language Processing Quiz Quiz NLP Medium Quiz 5 Pradip Devkar November 7, 2024 Natural Language Processing Quiz Quiz NLP Medium Quiz 4 Pradip Devkar November 7, 2024 Deep Learning Quiz Quiz Deep Learning Expert Quiz 10 Pradip Devkar November 6, 2024 Leave a Reply Cancel replyYou must be logged in to post a comment.
