Graham Neubig Courses

Neural Nets for NLP - Transition-based Parsing

Explore transition-based parsing for NLP, covering shift-reduce methods, Stack LSTM, phrase structure models, and linearized trees. Gain insights into advanced parsing techniques.

• YouTube
• 59 minutes
• On-Demand
• Free Video

Neural Nets for NLP - Latent Random Variables

Explore latent random variables in neural networks for NLP, covering variational autoencoders, discrete latent variables, and applications in language processing and text generation.

• YouTube
• 56 minutes
• On-Demand
• Free Video

CMU Neural Nets for NLP - Model Interpretation

Explore model interpretation in neural networks for NLP, covering themes, analysis techniques, and evaluation methods for understanding and explaining neural models.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Neural Nets for NLP - Structured Prediction with Local Independence Assumptions

Explore structured prediction in NLP using local independence assumptions and conditional random fields. Learn about sequence labeling, globally normalized models, and advanced training techniques.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Neural Nets for NLP 2019 - Reinforcement Learning

Explore reinforcement learning in NLP, covering policy gradient, REINFORCE, value-based methods, and applications in dialogue and information retrieval.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Neural Nets for NLP - Structured Prediction Basics

Explore structured prediction in NLP, covering perceptron algorithms, max-margin objectives, and exposure bias remedies. Learn techniques for modeling output interactions and training globally normalized models.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video

Neural Nets for NLP - Debugging Neural Nets

Practical strategies for identifying and resolving issues in neural networks for NLP, covering training and test-time problems, model architecture, and data analysis.

• YouTube
• 1 hour 15 minutes
• On-Demand
• Free Video

Neural Nets for NLP 2019: Sentence and Contextualized Word Representations

Explore sentence representations and contextual word embeddings for NLP tasks. Learn about multi-task learning, transfer learning, and pre-training techniques to improve model performance.

• YouTube
• 1 hour 18 minutes
• On-Demand
• Free Video

Neural Nets for NLP 2019 - Attention

Explore attention mechanisms in neural networks for NLP, covering basic concepts, improvements, specialized varieties, and a case study on the Transformer model.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

Neural Nets for NLP - Recurrent Networks for Sentence or Language Modeling

Explore recurrent networks, LSTMs, and their applications in sentence modeling and NLP. Learn about vanishing gradients, pre-training, and the strengths and weaknesses of recurrent models.

• YouTube
• 1 hour 12 minutes
• On-Demand
• Free Video

Neural Nets for NLP 2019 - Convolutional Neural Networks for Language

Explore convolutional neural networks for NLP, covering bag-of-words, context windows, sentence modeling, stacked and dilated convolutions, and structured convolution for sentence pairs.

• YouTube
• 1 hour 12 minutes
• On-Demand
• Free Video

Neural Nets for NLP 2019 - Word Vectors

Explore word embeddings, their training methods, evaluation techniques, and advanced concepts in natural language processing. Learn to represent words numerically for machine learning applications.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Neural Nets for NLP 2018 - Learning from-for Knowledge Graphs

Explore neural network techniques for knowledge graph construction, relation extraction, and embedding refinement in natural language processing.

• YouTube
• 52 minutes
• On-Demand
• Free Video

CMU Neural Nets for NLP 2018 - Document-Level Models

Explore document-level NLP models, covering language modeling, topic modeling, coreference resolution, and discourse parsing. Learn advanced techniques for analyzing and processing longer texts.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Neural Nets for NLP 2018 - Models of Dialogue

Explore models of dialogue in neural networks, covering generation-based approaches, discourse-level coherence, diversity promotion, evaluation methods, and personality infusion in conversational AI.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video