Transformers for natural language processing : build, train, and fine-tuning deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, and GPT-3 / Denis Rothman ; foreword by Antonio Gulli

By:

Rothman, Denis [author]

Contributor(s):

Material type: Text

TextSeries: Expert insightPublication details: [Birmingham, United Kingdom] : Packt Publishing, [2022]Edition: Second editionDescription: 1 online resource (564 pages) : illustrationsContent type:

text

Media type:

computer

Carrier type:

online resource

Subject(s):

Genre/Form:

Electronic books

DDC classification:

006.3 23 Ro Tr

LOC classification:

Q336

Online resources:

Safari Books Online Connect to resource

Summary: Transformers are a game-changer for natural language understanding (NLU) and have become one of the pillars of artificial intelligence. Transformers for Natural Language Processing, 2nd Edition, investigates deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question-answering, and many more NLP domains with transformers. An Industry 4.0 AI specialist needs to be adaptable; knowing just one NLP platform is not enough anymore. Different platforms have different benefits depending on the application, whether it's cost, flexibility, ease of implementation, results, or performance. In this book, we analyze numerous use cases with Hugging Face, Google Trax, OpenAI, and AllenNLP. This book takes transformers' capabilities further by combining multiple NLP techniques, such as sentiment analysis, named entity recognition, and semantic role labeling, to analyze complex use cases, such as dissecting fake news on Twitter. Also, see how transformers can create code using just a brief description. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models to various datasets

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Holdings
Item type	Current library	Collection	Call number	URL	Copy number	Status	Notes	Date due	Barcode
Books	Bahrain ITC-ARI	Computer Studies	006.3 Ro Tr (Browse shelf(Opens below))	Link to resource		Available	Dr. Hafiz Abid Malik		3000003977
Books	Bahrain ITC-ARI	Computer Studies	006.3 Ro Tr (Browse shelf(Opens below))	Link to resource	1	Available	Dr. Hafiz Abid Malik		3000003979

Includes index

Available to OhioLINK libraries

Transformers are a game-changer for natural language understanding (NLU) and have become one of the pillars of artificial intelligence. Transformers for Natural Language Processing, 2nd Edition, investigates deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question-answering, and many more NLP domains with transformers. An Industry 4.0 AI specialist needs to be adaptable; knowing just one NLP platform is not enough anymore. Different platforms have different benefits depending on the application, whether it's cost, flexibility, ease of implementation, results, or performance. In this book, we analyze numerous use cases with Hugging Face, Google Trax, OpenAI, and AllenNLP. This book takes transformers' capabilities further by combining multiple NLP techniques, such as sentiment analysis, named entity recognition, and semantic role labeling, to analyze complex use cases, such as dissecting fake news on Twitter. Also, see how transformers can create code using just a brief description. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models to various datasets

The online book link:

https://www.amazon.com/Transformers-Natural-Language-Processing-architectures/dp/1803247339/ref=sr_1_3?crid=840OBYTDU80Y&keywords=9781803247335&qid=1699255982&sprefix=9781803247335%2Caps%2C305&sr=8-3

Dr. Hafiz Abid Malik

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