Syntactic Parsing: Dependency Structure

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CLP Parser Lab Presentation

Covers implementing a parser for transforming tokens into an Abstract Syntax Tree.

Introduction to NLP and the Course

Covers the basics of Natural Language Processing, including challenges, linguistic processing levels, and the impact of power laws.

Context-Free Grammars: Part 1

Covers context-free grammars, production rules, automata, syntax analysis, and parsing techniques.

Parsing with Combinators

Explores parsing text into trees using parser combinators in Scala, covering filtering, transforming, sequencing, alternatives, recursion, spaces handling, lexing, monadic nature, and for-notation.

Compilers: Challenges with Digital Signal Processors

Covers the challenges of compiling for digital signal processors due to their unique architectural features and irregularities.

Chemical Reactions: Transformer Architecture

Explores atom mapping in chemical reactions and the transition to reaction grammar using the transformer architecture.

LL(1) Parsing

Covers LL(1) parsing, formalization, automation, constraints, and parsing tables.

Neural Networks for NLP

Covers modern Neural Network approaches to NLP, focusing on word embeddings, Neural Networks for NLP tasks, and future Transfer Learning techniques.

Model Analysis

Explores neural model analysis in NLP, covering evaluation, probing, and ablation studies to understand model behavior and interpretability.

Neural Model: Assemblies of Neurons and Language Acquisition

Explores a neural model, assemblies of neurons, language acquisition, and the future of neuromorphic intelligent systems.