Shengxiang-Lin/COMPSCI-288
UCB CS 288. Natural Language Processing
ArchivedImplements core NLP algorithms including n-gram language models, dependency parsing, named entity recognition, and sequence labeling with hidden Markov models. The coursework covers both statistical approaches and neural architectures, progressing from tokenization and POS tagging through structured prediction tasks. Assignments emphasize hands-on implementation of fundamental techniques rather than relying on high-level NLP libraries, building understanding of underlying mechanisms.
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