What is the MNIST dataset used for?

In which of the following cases does machine learning come into the picture?

Adding a non-important feature to a linear regression model will result in:

Which of the following hyperparameters, when increased, may cause a random forest model to overfit the data?

In a situation with multicollinear features, which of the following actions would you perform next?

Which of the following statements about Type-1 and Type-2 errors is/are true?

What are the three basic Machine Learning Paradigms?

Suppose we have a dataset that can be trained with 100% accuracy using a decision tree of depth 6. Now, consider the following points and choose the option that best describes the characteristics of a decision tree with depth 4:

What is Machine Learning?

Suppose you want to project high dimensional data into lower dimensions. The two most famous dimensionality reduction algorithms used here are Principal Component Analysis (PCA) and t-SNE. Let's say you have applied both algorithms respectively on data 'X' and you got the datasets 'X_projected_PCA' and 'X_projected_tSNE'. Which of the following statements is true for 'X_projected_PCA' and 'X_projected_tSNE'?