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Showing posts with the label Bayesian 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 πŸ‘‰ 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. πŸ‘‰ Machine Learning 2- UNIT-1 (A) Notes: Introduction & Concept Learning and the General to Specific Ordering Notes πŸ‘‰ Machine Learning 2 UNIT-1 (A) PPTs: Introduction PPTs πŸ‘‰ Machine L...

MACHINE LEARNING UNIT – 3 (A) PPT's (Bayesian Learning)

MACHINE LEARNING UNIT - 3 (A) NOTES (BAYESIAN LEARNING)