AL-702 (B) RGPV B.Tech
Advance Machine Learning (AML)
Previous year papers and the official syllabus are free to read, no account needed.
Previous Year Papers
1 paper, latest Dec 2025
Syllabus, notes and important questions for AL-702 (B)
Syllabus units
Topics as the official RGPV syllabus lists them.
Unit 1 Artificial Neural Network 7 topics
- Introduction to ANN
- Perceptron
- Cost Function
- Gradient Checking
- Multi-layer perceptron
- Backpropagation algorithm
- Random Initialization
Unit 2 Decision Trees 7 topics
- Representing concepts as decision trees
- Recursive induction of decision trees
- Best splitting attribute: entropy and information gain
- Searching for simple trees and computational complexity
- Overfitting
- Noisy data
- Pruning
Unit 3 Ensemble Methods 5 topics
- Bagging
- Boosting
- Stacking
- Learning with ensembles
- Random Forest
Unit 4 Reinforcement Learning 15 topics
- Introduction to reinforcement learning (RL)
- RL framework
- Markov Decision Process (MDP)
- Bellman equations
- Value Iteration
- Policy Iteration
- Actor-critic model
- Q-learning
- SARSA
- Bandit algorithms – UCB
- Bandit algorithms – PAC
- Bandit algorithms – Median Elimination
- Policy Gradient
- Full RL & MDPs
- Bellman Optimality
Unit 5 Dynamic Programming and Advanced RL Techniques 14 topics
- Dynamic Programming – Value iteration
- Policy iteration
- Q-learning & Temporal Difference Methods
- Temporal‑Difference Learning
- Eligibility Traces
- Function Approximation
- Least Squares Methods
- Fitted Q
- Deep Q‑Learning
- Advanced Q‑learning algorithms
- Inverse reinforcement learning
- Deep Inverse Reinforcement Learning
- Generative Adversarial Imitation Learning
- Recent Trends in RL Architectures