This module teaches SOTA NLP methods and applications. Students will learn about some of the most exciting new developments in modern NLP, such as Transformers and GPT-3.
DurationThis module teaches SOTA NLP methods and applications. Students will learn about some of the most exciting new developments in modern NLP, such as Transformers and GPT-3.
Learning Outcomes
Learn basic text-processing techniques
Become familiar with traditional NLP methods such as N-gram, topic modelling, text clustering, and NER
Learn word embedding techniques such as skip-gram and word2vec
Sequence-to-Sequence models with recurrent neural networks (RNN) and LSTM
Apply state-of-the-art (SOTA) attention models, such as BERT transformers for transfer learning
Apply generative models such as GPT-3 for text generation and Question-and-answer systems
Build a mini-ChatGPT application using GPT-3 and PyTorch
Key Skill:
Text Processing, Natural Language Processing, Large Langage Models (LLM), Topic Modeling, Transformers, BERT, GPT-3, Roberta, Text Classification, Sentiment Analysis, and Search Engine
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