Natural Language Processing and Information Extraction

- Basics of text processing: segmentation, tokenization, decompounding, stemming, lemmatization; regular expressions
- N-gram language modeling, simple classification tasks in NLP
- Part-of-speech tagging, named entity recognition, and shallow parsing with Hidden Markov Models
- Syntactic representations and syntactic parsing
- Basics of natural language semantics
- Neural network basics. Feed forward networks and recurrent neural networks
- Sequence modeling and sequence-to-sequence models. 
- Neural language modeling. Word vectors and contextualized language models. 
- Information extraction tasks: entity recognition, relation extraction, knowledge base population
- Information extraction applications: summarization, question answering, chatbots