Neural network methods in natural language processing
Series: Synthesis Lectures on Human Language TechnologiesPublication details: New york : Springer, ©2022Description: 287 p. : col. ill. ; 23 cmISBN:- 9783031010378
- 006.3 GOL-N
Item type | Current library | Collection | Call number | Status | Notes | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|---|
Books | IIITD Reference | Computer Science and Engineering | CB 006.3 GOL-N (Browse shelf(Opens below)) | Available | DBT Project Grant | 012929 |
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CB 006 CON-M Machine learning for hackers | CB 006.1 GIR-D Dynamical variational autoencoders : a comprehensive review | CB 006.3 DOR-N The nature of complex networks | CB 006.3 GOL-N Neural network methods in natural language processing | CB 006.3 HAM-G Graph representation learning | CB 006.3 KAM-T Transformers for machine learning : a deep dive | CB 006.3 KIS-A The age of AI : |
Learning 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
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