Deep learning models have gained widespread popularity for natural language processing (NLP) because of their ability to accurately generalize over a range of contexts and languages.
Transformer-based models, such as Bidirectional Encoder Representations from Transformers (BERT), have revolutionized NLP by offering accuracy comparable to human baselines on benchmarks like SQuAD for question-answer, entity recognition, intent recognition, sentiment analysis, and more.
The NVIDIA Deep Learning Institute (DLI) is offering instructor-led, hands-on training on how to use Transformer-based natural language processing models for text classification tasks, such as categorizing documents.
In the course, you’ll also learn how to use Transformer-based models for named-entity recognition (NER) tasks and how to analyze various model features, constraints, and? characteristics. The training will help developers? determine? which? model? is? best? suited? for? a? particular? use? case? based? on? metrics, domain specificity, and available resources.
By participating in this is workshop, you’ll be able to:
- Understand how word embeddings have rapidly evolved in NLP tasks, from?Word2Vec and recurrent neural network (RNN)-based embeddings to Transformer-based contextualized embeddings
- See how Transformer architecture features, especially self-attention, are used to create language models without RNNs
- Use self-supervision to improve the Transformer architecture in BERT, Megatron, and other variants for superior NLP results
- Leverage pre-trained, modern NLP models to solve multiple tasks such as t ext classification, NER, and question answering
- Manage inference challenges and deploy refined models for live applications
This workshop will be available to the public at the GPU Technology Conference, October 5-9. Spots are limited. Early Bird Rate ends Sept. 25. Register Now.
Learn more about this DLI workshop. See the NVIDIA DLI Remote Instructor-Led training experience in this short video.?Visit the NVIDIA DLI homepage for a full list of online and instructor-led training.
