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 What does batch normalization do in a neural network? It normalizes the input data before feeding it into the network It increases the number of neurons in a hidden layer It reduces overfitting by adding regularization It normalizes the activations of the previous layer in a mini-batch 2 / 10 What is the primary purpose of the ReLU activation function in neural networks? To reduce the size of the network To introduce non-linearity to the network To prevent overfitting To scale input values between 0 and 1 3 / 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 4 / 10 Which deep learning model is most commonly used for generating new data, like images or text? Generative Adversarial Networks (GAN) Multilayer Perceptrons (MLP) Recurrent Neural Networks (RNN) Convolutional Neural Networks (CNN) 5 / 10 Which of the following activation functions can help address the vanishing gradient problem? ReLU Sigmoid Tanh Leaky ReLU 6 / 10 What is a dropout layer in deep learning? A layer used to reduce dimensionality of data A layer that drops input features A layer that randomly drops neurons during training to prevent overfitting A layer that removes noisy data from the input 7 / 10 Which of the following is an unsupervised learning technique used in deep learning? Decision Trees Support Vector Machines Autoencoders K-means clustering 8 / 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 Sharing parameters between two models Training a model from scratch on a new dataset 9 / 10 In a neural network, what is the purpose of the weight initialization technique? To prevent vanishing or exploding gradients To speed up convergence during training To ensure accurate predictions from the start To reduce the size of the model 10 / 10 Which of the following models is primarily used for sequential data? Recurrent Neural Networks (RNN) Feedforward Neural Networks Generative Adversarial Networks (GAN) Convolutional Neural Networks (CNN) 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 Artificial Intelligence Deep Learning Gen AI Machine Learning Natural Language Processing Projects Technology DriveXpert AI Assistant : Users quickly solve their car-related queries balugorad January 15, 2025 Artificial Intelligence Open Source vs Paid Large Language Models (LLMs): A Strategic Comparison balugorad January 15, 2025 Artificial Intelligence Deep Learning Gen AI Vector Databases: A Key Component in Modern AI and Data Science balugorad January 9, 2025 Leave a Reply Cancel replyYou must be logged in to post a comment.
