Advance Machine Learning (AL-702 (B)) - Important Questions

Define Artificial Neural Networks. What is the role of the cost function in training Artificial Neural Networks?

Describe the role of gradient descent in the backpropagation process and how it influences weight updates.

Describe the architecture and learning process of a multi-layer perceptron.

What is recursive induction in decision trees? Explain.

Define entropy and information gain. Calculate the overall entropy and information gain with the following dataset.

How does noisy data affect decision tree performance? Write the strategies to overcome them.

Compare Bagging and Boosting techniques in ensemble learning.

Describe the working mechanism of a Random Forest algorithm.

Why ensemble methods offer greater robustness compared to individual models? Discuss.

Explain the Bellman Equations in the context of Reinforcement Learning.

Differentiate between Q-learning and SARSA algorithms.

Describe the concept of Policy Gradient methods in Reinforcement Learning.

What is temporal difference learning and how does it differ from Monte Carlo methods?

How does Generative Adversarial Imitation learning differ from standard RL approaches?

Write short note on any two: