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Transformers for Natural Language Processing Build innovative deep neural network architectures for NLP

Transformers for Natural Language Processing Build innovative deep neural network architectures for NLP
Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch. BERT, RoBERTa, T5, GPT-2, architecture of GPT-3, and much more
by Denis Rothman

English | 2021 | ISBN: 1800565798 | 355 Pages | True PDF EPUB | 9 MB


The Transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains in context with the Transformers.



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