000			01392 a2200217 4500
003			IIITD
005			20240427150308.0
008			240425b |||||||| |||| 00| 0 eng d
020			_a9783031010378
040			_aIIITD
082			_a006.3 _bGOL-N
100			_aGoldberg, Yoav
245			_aNeural network methods in natural language processing _cby Yoav Goldberg
260			_aNew york : _bSpringer, _c©2022
300			_a287 p. : _bcol. ill. ; _c23 cm.
440			_aSynthesis Lectures on Human Language Technologies
505			_tLearning Basics and Linear Models From Linear Models to Multi-layer Perceptrons Feed-forward Neural Networks Neural Network Training Features for Textual Data Case Studies of NLP Features From Textual Features to Inputs Language Modeling Pre-trained Word Representations Using Word Embeddings Case Study: A Feed-forward Architecture for Sentence Case Study: A Feed-forward Architecture for Sentence Meaning Inference Ngram Detectors: Convolutional Neural Networks Recurrent Neural Networks: Modeling Sequences and Stacks Concrete Recurrent Neural Network Architectures Modeling with Recurrent Networks Conditioned Generation Modeling Trees with Recursive Neural Networks Structured Output Prediction Cascaded, Multi-task and Semi-supervised Learning
650			_aArtificial intelligence
650			_aComputational linguistics
942			_2ddc _cBK
999			_c172591 _d172591