ROUND 2

In reinforcement learning, what does the term "policy" refer to?

• A set of rules defining the rewards

• The agent's strategy for selecting actions

• The environment's response to actions

• The state transition probabilities

In natural language processing, what is the purpose of "word embeddings"?

• To visualize word frequencies in a document

• To reduce the dimensionality of text data

• To represent words as dense vectors in a continuous space

• To perform sentiment analysis on text data

Which optimization algorithm is commonly used for training deep neural networks and adapts the learning rate for each parameter?

• Gradient Descent

• AdaGrad

• Adam

• RMSprop

Which of the following libraries in Python is primarily used for deep learning tasks?

• NumPy

• Matplotlib

• TensorFlow

• Scikit-learn

Which of the following is NOT a dimensionality reduction technique?

• Principal Component Analysis (PCA)

• Linear Discriminant Analysis (LDA)

• K-Means Clustering

• t-Distributed Stochastic Neighbor Embedding (t-SNE)

Which of the following is NOT a type of artificial neural network architecture?

• Convolutional Neural Network (CNN)

• Recurrent Neural Network (RNN)

• Decision Tree

• Generative Adversarial Network (GAN)

What does the term "bagging" refer to in ensemble learning?

• Training multiple models sequentially

• Training multiple models in parallel

• Aggregating predictions from multiple models

• Boosting the performance of individual models

Which activation function is commonly used in the output layer of a binary classification neural network?

• ReLU

• Sigmoid

• Tanh

• Leaky ReLU

Which technique is used to address the problem of vanishing gradients in deep neural networks?

• L1 regularization

• Batch normalization

• Dropout

• Stochastic gradient descent

In hierarchical clustering, what is the purpose of a dendrogram?

• It visualizes the decision boundaries of the clustered data

• It represents the distance between cluster centroids

• It displays the hierarchical relationships between clusters and data points

• It computes the silhouette scores for evaluating cluster quality