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Explore neural networks for NLP with Graham Neubig's online material. Learn to identify training problems, debug decoding, manage loss function, and prevent overfitting in under an hour.
Explore Recurrent Neural Networks (RNNs) for Natural Language Processing (NLP) with Graham Neubig's online material. Expect 1-2 hours of study on topics like LSTM structure, mini-batching, and more.
Explore the world of Neural Nets for NLP with Graham Neubig's online program. Learn about word embeddings, training methods, evaluation types, and limitations in just 1-2 hours.
Explore multitask learning, domain adaptation, and multilingual learning in Neural Networks for NLP with Graham Neubig. Less than 1-hour workload.
Explore advanced search algorithms like Beam Search and A*-type Search in Neural Networks for NLP with this 1-2 hour material by Graham Neubig.
Learn to debug neural networks for NLP with Graham Neubig's 1-2 hour material, covering problem diagnosis, training and decoding issues, and overfitting combat.
Explore neural networks for NLP with Graham Neubig's 1-2 hour material, covering chat-based and task-based dialog models, response generation, and dialog state tracking.
Explore Neural Networks for NLP with Graham Neubig's material, covering coreference models, discourse parsing, and document level prediction in 1-2 hours.
Explore unsupervised learning of structure in Neural Networks for NLP with Graham Neubig. Less than 1-hour material covering learning methods, design decisions, and examples.
Explore unsupervised and semi-supervised learning of structure in NLP with Graham Neubig's 1-2 hour material, covering design decisions, examples, and methods.
Explore Neural Networks for NLP with Graham Neubig's 1-2 hour material, covering generative models, variational autoencoders, and latent variable handling.
Explore structured prediction, perceptron algorithms, and remedies to exposure bias in this 1-2 hour material by Graham Neubig.
Explore advanced search algorithms in Neural Networks for NLP with Graham Neubig's 1-2 hour material, covering topics like Beam Search, Minimum Bayes risk, and Sampling-based search.
Explore Neural Networks for NLP with Graham Neubig's 1-2 hour material, covering Minimum Risk Training, Reinforcement Learning, and Policy Gradient.
Explore transition-based parsing, shift-reduce parsing with feed-forward nets, and semantic parsing in this 1-2 hour material by Graham Neubig.
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