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Machine Learning2 - UNIT-2(B) Notes: Artificial Neural Networks Notes

UNIT – II (B) Artificial Neural Networks Introduction Neural Network Representation Appropriate Problems for Neural Network Learning Perceptron’s Multilayer Networks The Back-Propagation Algorithm

Machine Learning

Machine Learning2 - UNIT 2(B) PPTs : Artificial Neural Networks PPTs

UNIT – II (B) Artificial Neural Networks Introduction Neural Network Representation Appropriate Problems for Neural Network Learning Perceptron’s Multilayer Networks and the Back-Propagation Algorithm.

Machine Learning

Machine Learning 2 - UNIT-2 (A) PPTs : Decision Tree Learning PPTs

UNIT-2 (A) Decision Tree Learning Decision Tree Learning : Introduction Decision Tree Representation Appropriate Problems for Decision Tree Learning The Basic Decision Tree Learning Algorithm Issues In Decision Tree Learning

Machine Learning

Machine Learning 2 - UNIT-2 (A) NOTEs: Decision Tree Learning Notes

UNIT-2 (A) Decision Tree Learning Decision Tree Learning: Introduction Decision Tree Representation Appropriate Problems for Decision Tree Learning The Basic Decision Tree Learning Algorithm Issues In Decision Tree Learning

Machine Learning

Machine Learning 2- UNIT-1 (B) Concept Learning and the General to Specific Ordering PPTs

UNIT-1 (B) Concept Learning and the General to Specific Ordering Concept Learning and the General to Specific Ordering Introduction A Concept Learning Task Concept Learning as Search Find-S: Finding a Maximally Specific Hypothesis Version Spaces and the Candidate Elimination Algorithm

Machine Learning

Machine Learning 2 UNIT-1 (A) PPTs: Introduction PPTs

UNIT-1 (A) Introduction Introduction: Well-Posed Learning Problems Designing a Learning System Perspectives and Issues in Machine Learning Introduction to Supervised Unsupervised and Reinforcement Learning

Machine Learning

Machine Learning 2- UNIT-1 (A) Notes : Introduction & Concept Learning and the General to Specific Ordering Notes

UNIT-1 Introduction & Concept Learning and the General to Specific Ordering Introduction: Well-Posed Learning Problems Designing a Learning System Perspectives and Issues in Machine Learning Introduction to Supervised Unsupervised and Reinforcement Learning Concept Learning and the General to Specific Ordering: Introduction A Concept Learning Task Concept Learning as Search Find-S: Finding a Maximally Specific Hypothesis Version Spaces and the Candidate Elimination Algorithm

Machine Learning

About Machine Learning 2

Machine Learning Introduction Concept Learning and the General to Specific Ordering Decision Tree Learning Artificial Neural Networks Bayesian Learning Instance-Based Learning Genetic Algorithms Learning Sets of Rules Analytical Learning Reinforcement Learning 👉 Machine Learning 2 Syllabus UNIT-1 : Introduction & Concept Learning and the General to Specific Ordering Introduction - Well-Posed Learning Problems, Designing a Learning System, Perspectives and Issues in Machine Learning, Introduction to Supervised, Unsupervised and Reinforcement Learning. Concept Learning and the General to Specific Ordering – Introduction, A Concept Learning Task, Concept Learning as Search, Find-S: Finding a Maximally Specific Hypothesis, Version Spaces and the Candidate Elimination Algorithm. 👉 Machine Learning 2- UNIT-1 (A) Notes: Introduction & Concept Learning and the General to Specific Ordering Notes 👉 Machine Learning 2 UNIT-1 (A) PPTs: Introduction PPTs 👉 Machine Learning 2- UNI

Machine Learning