Data and Analytics Machine Learning Fundamentals 2

Question 1

Which algorithm builds an ensemble of decision trees using random subsets of features and training samples?

Accepted Answer

Random Forest

Answer

Random Forest creates multiple decision trees using random feature subsets and bootstrap samples, then aggregates their predictions to improve accuracy and reduce overfitting.

Question 2

In a neural network, what is the role of an activation function?

Accepted Answer

To introduce non-linearity so the network can learn complex patterns

Answer

Activation functions introduce non-linearity into neural networks, enabling them to learn and represent complex, non-linear relationships in data.

Question 3

What is gradient descent used for in machine learning?

Accepted Answer

Iteratively updating model parameters to minimize the loss function

Answer

Gradient descent is an optimization algorithm that iteratively adjusts model parameters in the direction that minimizes the loss function, guided by the gradient.

Question 4

Which type of machine learning is used in recommendation systems where an agent learns by receiving rewards or penalties?

Accepted Answer

Reinforcement learning

Answer

Reinforcement learning trains an agent to make decisions by rewarding desired actions and penalizing undesired ones, making it well-suited for sequential decision-making tasks.

Question 5

What does PCA (Principal Component Analysis) primarily accomplish in data analysis?

Accepted Answer

Reduces dimensionality by projecting data onto principal components

Answer

PCA reduces the number of features by projecting data onto orthogonal axes (principal components) that capture the most variance, simplifying analysis without losing critical information.

Data and Analytics Practice Test

Data and Analytics Practice Test

Data and Analytics Machine Learning Fundamentals 2