- Supervised Learning
- Classification
- Regression
- Time Series Forecasting
- Unsupervised Learning
- Clustering
- K-Means Clustering
- Hierarchical Clustering
- Semi-Supervised Learning
- Reinforcement Learning(ML)
- Deep Learning(ML)
- Transfer Learning(ML)
- Ensemble Learning
- Explainable AI (XAI)
- Bayesian Learning
- Decision Trees
- Support Vector Machines (SVMs)
- Instance-Based Learning
- Rule-Based Learning
- Neural Networks
- Evolutionary Algorithms
- Meta-Learning
- Multi-Task Learning
- Metric Learning
- Few-Shot Learning
- Adversarial Learning
- Data Pre Processing
- Natural Language Processing(ML)

# Bayesian Learning QUIZ - MCQ QUESTIONS AND ANSWERS

Question: 1

## What is the main disadvantage of Bayesian learning compared to frequentist learning?

Question: 2

## In the context of Bayesian learning, what is a "conjugate prior"?

Question: 3

## What is the purpose of the Bayesian Information Criterion (BIC)?

Question: 4

## In the context of Bayesian learning, what is "evidence"?

Question: 5

## What is a Bayesian network?

Question: 6

## What is the primary purpose of Markov Chain Monte Carlo (MCMC) methods in Bayesian learning?

Question: 7

## Which of the following is a popular MCMC sampling method in Bayesian learning?

Question: 8

## In Bayesian learning, what is "model averaging"?

Question: 9

## What is the main difference between Bayesian and Maximum Likelihood Estimation (MLE)?

Question: 10

## In the context of Bayesian learning, what is the "marginal likelihood"?

Question: 11

## What is the main advantage of using variational inference over MCMC methods in Bayesian learning?

Question: 12

## Which of the following is a popular variational inference method in Bayesian learning?

Question: 13

## Bayesian network, what does the "Markov blanket" of a variable represent?

Question: 14

## What is the purpose of the Dirichlet Process in Bayesian learning?

Question: 15

## What is the main disadvantage of using Bayesian methods for online learning?

Question: 16

## In Bayesian learning, what is the "maximum a posteriori" (MAP) estimate?

Question: 17

## What is the purpose of using the Laplace approximation in Bayesian learning?

Question: 18

## What is a Gaussian Process in the context of Bayesian learning?

Question: 19

## Which of the following is an advantage of using Gaussian Processes in Bayesian learning?

Question: 20

## What is the purpose of the Reversible Jump MCMC (RJ-MCMC) method in Bayesian learning?

Question: 21

## What is the main advantage of Bayesian optimization?

Question: 22

## In the context of Bayesian learning, what is an "active learning" strategy?

Question: 23

## Which of the following is a popular Bayesian optimization algorithm?

Question: 24

## What is the main disadvantage of using Gaussian Processes in Bayesian learning?

Question: 25

## In the context of Bayesian learning, what is "epistemic uncertainty"?

Question: 26

## What is the primary principle of Bayesian learning?

Question: 27

## Which theorem is the foundation of Bayesian learning?

Question: 28

## In Bayesian learning, what is the "prior probability"?

Question: 29

## In Bayesian learning, what is the "posterior probability"?

Question: 30