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Acknowledgement: Some of the slides are borrowed (with modifications) from the course by Prof. Pawan Goyal (IIT Kharagpur) and the Stanford NLP course by Prof. Chris Manning and others.
NLP01-what-is-nlp.pdfNLP02-why-is-nlp-hard.pdfNLP03-empirical-laws.pdfNLP04-text-processing-basics.pdfNLP05-spelling-correction.pdfNLP06-ngram-lang-model.pdfNLP07-evaluate-lang-model.pdfNLP08-POS-tagging-intro.pdfNLP09-HMMs-for-POS-tagging.pdfNLP10-Viterbi-for-HMM.pdfNLP11-syntax-intro-CFG.pdfSyntax: Introduction
Syntax: Introduction
NLP12-constituency-parsing.pdfSyntax: Constituency parsing
Syntax: Constituency parsing
NLP13-dependency-grammar-parsing.pdfSyntax: Dependency Graphs
Syntax: Dependency Graphs
NLP14-transition-based-parsing-formulation.pdfTransition-based Parsing: Formulation
Transition-based Parsing: Formulation
NLP15-transition-based-parsing-learning.pdfTransition-based Parsing: Learning
Transition-based Parsing: Learning
NLP16-distributional-semantics.pdfDistributional Semantics
Distributional Semantics
NLP17-word-embeddings.pdfWord Embeddings
Word Embeddings
NLP18-RNNs.pdfRecurrent Neural Networks
Recurrent Neural Networks
NLP19-advancedRNNs.pdfAdvanced RNNs
Advanced RNNs
NLP20-seq2seq-attention.pdfSequence-to-sequence and Attention
Sequence-to-sequence and Attention
NLP21a-Transformers.pdfTransformers I
Transformers I
NLP21b-attention-is-all-you-need-NIPS17.pdfTransformers II
Transformers II
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