Sequence Labeling Courses and Certifications

Graham Neubig

CMU Multilingual NLP 2020 - Text Classification and Sequence Labeling

Explore text classification and sequence labeling in multilingual NLP, covering models, datasets, and neural networks for various language processing tasks.

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

NPTEL;  IIT Bombay

Natural Language Processing

This course provides an understanding of natural language processing, its tools, techniques, philosophy and principle. Topics covered include sound, words and word forms, structures, meaning, and web 2.0 applications

• YouTube
• 1 day 8 hours
• On-Demand
• Free Video

Graham Neubig

Neural Nets for NLP 2021 - Structured Prediction with Local Independence Assumptions

Explore structured prediction in NLP, focusing on local independence assumptions and Conditional Random Fields. Learn about sequence labeling, potential functions, and dynamic programming models.

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

Graham Neubig

CMU Multilingual NLP 2020 - Advanced Text Classification-Labeling

Explore advanced text classification and sequence labeling methods, including subword models, unsupervised training, and structured prediction for multilingual NLP applications.

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

Graham Neubig

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

Graham Neubig

Neural Nets for NLP 2020 - Structured Prediction with Local Independence Assumptions

Explore structured prediction in NLP, covering local independence assumptions and Conditional Random Fields for improved sequence labeling and output consistency.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

Graham Neubig

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

Graham Neubig

CMU Neural Nets for NLP - Structured Prediction Basics

Explore structured prediction in NLP, covering sequence labeling, model interactions, training algorithms, and cost-augmented decoding for improved language understanding and generation.

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

Association for Computing Machinery (ACM)

Scientific Text Mining and Knowledge Graphs

Explore scientific text mining and knowledge graphs, focusing on sequence labeling, multi-output models, and ensemble learning for information extraction and table component analysis.

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

Center for Language & Speech Processing(CLSP), JHU

Style Transfer for Data Augmentation in Sequence Labelling Tasks - September 2022

Explore style transfer for data augmentation in sequence labeling tasks, focusing on named entity recognition in social media. Learn about improving domain adaptation and addressing data scarcity.

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

Center for Language & Speech Processing(CLSP), JHU

New Machine Learning Tools for Structured Prediction

Discover new machine learning tools for structured prediction in this technical seminar by Veselin Stoyanov from Johns Hopkins HLTCOE.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video