Sequence Modeling with Recurrent Neural Network

Sequence modeling is a fundamental problem in Natural Language Processing (NLP) due to the sequential nature of language. With advances in Recurrent Neural Networks, this family of models has become the state-of-the-art for many sequence mapping tasks. In this thesis, we examine the effectiveness of this family of models for several classes of problems in NLP.