Course Materials
W1L2.pdfWhat is NLP?
What is NLP?
W1L3.pdfWhy is NLP hard?
Why is NLP hard?
W2L1.pdfEmpirical Laws
Empirical Laws
W3L1.pdfText Processing: Basics
Text Processing: Basics
W4L1.pdfN-gram Language Model
N-gram Language Model
W4L2.pdfEvaluation of Language Models, Basic Smoothing
Evaluation of Language Models, Basic Smoothing
W4L3.pdfLanguage Modeling: Advanced Smoothing Models
Language Modeling: Advanced Smoothing Models
W5L1.pdfPart-of-Speech (POS) tagging
Part-of-Speech (POS) tagging
W5L2.pdfHMM for POS tagging
HMM for POS tagging
W5L3.pdfViterbi Decoding for HMM, Parameter Learning
Viterbi Decoding for HMM, Parameter Learning
W6L1.pdfSyntax - Introduction
Syntax - Introduction
W6L2.pdfDependency Grammars and Parsing
Dependency Grammars and Parsing
W6L3.pdfTransition based Parsing : Formulation
Transition based Parsing : Formulation
W7L1.pdfTransition based Parsing : Learning
Transition based Parsing : Learning
W7L2.pdfDistributional Semantics : Word vectors
Distributional Semantics : Word vectors
Attention_1.pptxAttention-1
Attention-1
Attention_2.pptxAttention-2
Attention-2
lec02_rnn-3-41.pdfRNN (Courtesy: Dr Arun Mallaya)
RNN (Courtesy: Dr Arun Mallaya)
RNNs_seq2seq-2-42.pdfRNN : Sequence-to-Sequence
RNN : Sequence-to-Sequence
11.1. Queries, Keys, and Values — Dive into Deep Learning 1.0-merged-compressed.pdfTransformers
Transformers
