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Explores methods for information extraction, including traditional and embedding-based approaches, supervised learning, distant supervision, and taxonomy induction.
Explores model selection, evaluation, and generalization in machine learning, emphasizing unbiased performance estimation and the risks of over-learning.
Explores document retrieval, classification, sentiment analysis, and topic detection in text analysis using supervised learning and bag-of-words models.
