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CS8082 Machine Learning Techniques Syllabus Notes Question Banks with answers

CS8082 Machine Learning Techniques Syllabus Notes Question Paper Question Banks with answers Anna University

Anna University Machine Learning Techniques Syllabus Notes Question Bank Question Papers Regulation 2017

Anna University CS8082 Machine Learning Techniques Notes are provided below. CS8082 Notes all 5 units notes are uploaded here. here CS8082 Machine Learning Techniques notes download link is provided and students can download the CS8082 MLT Lecture Notes and can make use of it.
CS8082 Machine Learning Techniques Syllabus Notes


CS8082 Machine Learning Techniques Syllabus Regulation 2017

UNIT I INTRODUCTION
Learning Problems – Perspectives and Issues – Concept Learning – Version Spaces and Candidate Eliminations – Inductive bias – Decision Tree learning – Representation – Algorithm – Heuristic Space Search.
UNIT II NEURAL NETWORKS AND GENETIC ALGORITHMS
Neural Network Representation – Problems – Perceptrons – Multilayer Networks and Back Propagation Algorithms – Advanced Topics – Genetic Algorithms – Hypothesis Space Search – Genetic Programming – Models of Evaluation and Learning.
UNIT III BAYESIAN AND COMPUTATIONAL LEARNING
Bayes Theorem – Concept Learning – Maximum Likelihood – Minimum Description Length Principle – Bayes Optimal Classifier – Gibbs Algorithm – Na├»ve Bayes Classifier – Bayesian Belief Network – EM Algorithm – Probability Learning – Sample Complexity – Finite and Infinite Hypothesis Spaces – Mistake Bound Model.
UNIT IV INSTANT BASED LEARNING
K- Nearest Neighbour Learning – Locally weighted Regression – Radial Bases Functions – Case Based Learning.
UNIT V ADVANCED LEARNING
Learning Sets of Rules – Sequential Covering Algorithm – Learning Rule Set – First Order Rules – Sets of First Order Rules – Induction on Inverted Deduction – Inverting Resolution – Analytical Learning – Perfect Domain Theories – Explanation Base Learning – FOCL Algorithm – Reinforcement Learning – Task – Q-Learning – Temporal Difference Learning
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