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 is an example of a Recurrent Neural Network (RNN) application? Predicting stock prices based on past data Object detection in images Machine translation Image classification 2 / 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 achieves high accuracy on both training and test data When the model takes too long to train 3 / 10 Which of the following are common types of neural network layers? Recurrent layers Decision tree layers Pooling layers Convolutional layers 4 / 10 What is backpropagation in deep learning? A technique for generating new data A method used to update weights by calculating gradients A model evaluation technique A method for adding new layers to a neural network 5 / 10 In a Convolutional Neural Network (CNN), what is the purpose of pooling layers? To increase the number of parameters in the model To reduce the dimensionality of the feature maps To connect neurons to each other To perform activation functions like ReLU 6 / 10 Which of the following optimizers are commonly used in deep learning? Adam Stochastic Gradient Descent (SGD) Random Forest Naive Bayes 7 / 10 Which of the following techniques can help prevent overfitting in deep learning models? Early stopping Dropout Data augmentation Increasing the learning rate 8 / 10 What is an epoch in deep learning? One complete pass through the entire training dataset A single update to a neural network's weights The number of neurons in a hidden layer The time taken to train a model 9 / 10 What is the purpose of a loss function in deep learning? To increase the training speed of the model To measure how well the model predicts the output To initialize weights in the network To backpropagate errors through the network 10 / 10 What does the softmax function do in a neural network? Reduces overfitting in deep learning models Increases the number of layers in the network Applies an activation function for regression problems Converts raw outputs into probabilities 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 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.
