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Machine Learning Generative and Discriminative Models
1. What is Machine Learning? ML applications, ML as Search 2. Generative and Discriminative Taxonomy 3. Generative-Discriminative Pairs Classifiers: Naïve Bayes and Logistic Regression Sequential Data: HMMs and CRFs 4. Performance Comparison in Sequential Applications NLP: Table extraction, POS tagging, Shallow parsing, Handwritten word recognition, Document analysis 5. Advantages, disadvantages
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