Syntactic Parsing: Dependency Structure

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Page 3 of 4

The Future: Computational Linguistics and Deep Learning

Explores the influence of computational linguistics on deep learning architectures, covering grammar formalisms, connectionism, variable binding, and future directions.

Object-Oriented Parser Combinators

Covers object-oriented parser combinators in Scala for building parsers, including JSON parsing and testing.

Foundations of Software: Modeling Programming Languages

Covers the mathematical study of program behaviors, parsing, domain-specific languages, and powerful tools for language design.

Introduction to Computer Language Processing

Covers computer language processing, compilers, skills learned, and application examples.

Neural Networks: Two Layers Neural Network

Covers the basics of neural networks, focusing on the development from two layers neural networks to deep neural networks.

Language Models: Fixed-context and Recurrent Neural Networks

Discusses language models, focusing on fixed-context neural models and recurrent neural networks.

Sequence to Sequence Models: Overview and Applications

Covers sequence to sequence models, their architecture, applications, and the role of attention mechanisms in improving performance.

Deep Learning for Question Answering

Explores deep learning for question answering, analyzing neural networks and model robustness to noise.

Multi-layer Neural Networks

Covers the fundamentals of multi-layer neural networks and the training process of fully connected networks with hidden layers.

Neural Networks: Training and Optimization

Explores the training and optimization of neural networks, addressing challenges like non-convex loss functions and local minima.