{"description":"Test your understanding of deep learning fundamentals, neural networks, and the XOR problem using TensorFlow and PyTorch.","questions":[{"answer":"To train multi-layer neural networks for hierarchical representation learning","number":1,"options":["To enhance web development frameworks","To analyze structured data only","To train multi-layer neural networks for hierarchical representation learning","To build rule-based expert systems"],"question":"What is the primary goal of deep learning?"},{"answer":"NumPy","number":2,"options":["TensorFlow","Keras","NumPy","PyTorch"],"question":"Which of the following is NOT a deep learning framework?"},{"answer":"It cannot model non-linear relationships","number":3,"options":["It uses too much memory","It cannot model non-linear relationships","It cannot handle numerical data","It requires supervised labels"],"question":"In the XOR problem, why is a single-layer network insufficient?"},{"answer":"To measure the error between predictions and actual outputs","number":4,"options":["To visualize the model predictions","To connect layers of the neural network","To measure the error between predictions and actual outputs","To determine the input size"],"question":"What is the role of the loss function during model training?"},{"answer":"Stochastic Gradient Descent (SGD)","number":5,"options":["Adam","RMSProp","Adagrad","Stochastic Gradient Descent (SGD)"],"question":"What optimizer is used in the XOR examples provided in both TensorFlow and PyTorch?"},{"answer":"Sigmoid","number":6,"options":["Tanh","Softmax","Sigmoid","ReLU"],"question":"What activation function is used in the output layer of the XOR neural network?"},{"answer":"It allows dynamic computation graphs for flexibility","number":7,"options":["It uses a static computation graph","It is more suitable for web development","It allows dynamic computation graphs for flexibility","It requires less training data"],"question":"What is a key advantage of PyTorch over TensorFlow?"}],"title":"Introduction to Deep Learning"}