Artificial Intelligence Deep Learning Deep Learning Quiz Quiz Deep Learning Basics Quiz 2 Data AI Admin October 9, 2024 Welcome to the Deep Learning Basics Quiz 2! 🚀This quiz will further explore key deep learning concepts like optimizers, CNN layers, overfitting, and loss functions. Keep your deep learning knowledge sharp, and good luck! ⏰ Time's Up!Your quiz has ended, and your answers have been automatically submitted. Let’s see how much progress you’ve made in deep learning! Deep Learning Basics Quiz 2 This is the second quiz in the Deep Learning Basics series. It contains 10 multiple-choice questions designed to test your understanding of advanced topics like optimization, regularization, CNNs, and RNNs. Some questions may have more than one correct answer to help deepen your knowledge 1 / 10 Which of the following techniques can help prevent overfitting in deep learning models? Early stopping Dropout Increasing the learning rate Data augmentation 2 / 10 Which of the following are common types of neural network layers? Recurrent layers Pooling layers Decision tree layers Convolutional layers 3 / 10 What is backpropagation in deep learning? A method used to update weights by calculating gradients A model evaluation technique A method for adding new layers to a neural network A technique for generating new data 4 / 10 Which of the following is an example of a Recurrent Neural Network (RNN) application? Image classification Object detection in images Predicting stock prices based on past data Machine translation 5 / 10 In a Convolutional Neural Network (CNN), what is the purpose of pooling layers? To perform activation functions like ReLU To increase the number of parameters in the model To reduce the dimensionality of the feature maps To connect neurons to each other 6 / 10 What does the softmax function do in a neural network? Increases the number of layers in the network Reduces overfitting in deep learning models Converts raw outputs into probabilities Applies an activation function for regression problems 7 / 10 What is the purpose of a loss function in deep learning? To backpropagate errors through the network To increase the training speed of the model To measure how well the model predicts the output To initialize weights in the network 8 / 10 Which of the following optimizers are commonly used in deep learning? Naive Bayes Stochastic Gradient Descent (SGD) Random Forest Adam 9 / 10 What is an epoch in deep learning? One complete pass through the entire training dataset The number of neurons in a hidden layer The time taken to train a model A single update to a neural network's weights 10 / 10 What is overfitting in deep learning models? When the model's complexity is reduced When the model performs well on training data but poorly on unseen data When the model takes too long to train When the model achieves high accuracy on both training and test data Your score isThe average score is 60% 0% Restart quiz Share this… Whatsapp Linkedin Facebook Twitter Gmail Related Tags: Deep Learning, Deep Learning Quiz, Quiz Continue Reading Previous NLP Basics Quiz 3Next Deep Learning Basics Quiz 3 More Stories Artificial Intelligence AI Agent : A Personalized Chatbot Using LangGraph and LangChain balugorad April 8, 2025 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 Leave a Reply Cancel replyYou must be logged in to post a comment.
