What is 'cross-validation' in machine learning?
Response:

• A. A method for testing the model's performance on unseen data
• B. A process for combining predictions from different models
• C. A strategy for handling missing data
• D. A technique for tuning hyperparameters

P-values in hypothesis testing are used to:
Response:

• A. Determine the practical significance of results
• B. Visualize the distribution of data
• C. Estimate the probability of observing the data given the null hypothesis is true
• D. Calculate the mean of the data sample

In machine learning, what is 'bias-variance tradeoff'?
Response:

• A. The relationship between the model's complexity and its performance on unseen data
• B. The balance between the number of features and the size of the dataset
• C. The tradeoff between the learning rate and the number of epochs
• D. The compromise between the model's ability to generalize and its accuracy on training data

What is 'natural language processing' (NLP) in the context of machine learning?
Response:

• A. The process of converting text data into numerical data
• B. The field that focuses on the interaction between computers and human language
• C. A method for improving the accuracy of neural networks
• D. A technique for training models on time-series data

In the context of machine learning, what is a 'loss function' used for?
Response:

• A. To evaluate the performance of the model
• B. To increase the speed of training
• C. To reduce the memory usage of the model
• D. To select the most important features of the data