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AL-702 (B) Advance Machine Learning Notes

5 notes for Advance Machine Learning, unit by unit.

Unit 1 · Short notes Artificial Neural Network Introduction to ANN · Perceptron · Cost Function · Gradient Checking · Multi-layer perceptron · Backpropagation algorithm
Unit 2 · Short notes Decision Trees 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
Unit 3 · Short notes Ensemble Methods Bagging · Boosting · Stacking · Learning with ensembles · Random Forest
Unit 4 · Short notes Reinforcement Learning Introduction to reinforcement learning (RL) · RL framework · Markov Decision Process (MDP) · Bellman equations · Value Iteration · Policy Iteration
Unit 5 · Short notes Dynamic Programming and Advanced RL Techniques Dynamic Programming – Value iteration · Policy iteration · Q-learning & Temporal Difference Methods · Temporal‑Difference Learning · Eligibility Traces · Function Approximation

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