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Transformers for Natural Language Processing Build Innovative Deep Neural Network Architectures for NLP with Python, Pytorch, TensorFlow, BERT, RoBERTa, and More.
Being the first book in the market to dive deep into the Transformers, it is a step-by-step guide for data and AI practitioners to help enhance the performance of language understanding and gain expertise with hands-on implementation of transformers using PyTorch, TensorFlow, Hugging Face, Trax, and...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited,
2021.
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| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
MARC
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| 245 | 1 | 0 | |a Transformers for Natural Language Processing |h [electronic resource] : |b Build Innovative Deep Neural Network Architectures for NLP with Python, Pytorch, TensorFlow, BERT, RoBERTa, and More. |
| 260 | |a Birmingham : |b Packt Publishing, Limited, |c 2021. | ||
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| 500 | |a Description based upon print version of record. | ||
| 520 | |a Being the first book in the market to dive deep into the Transformers, it is a step-by-step guide for data and AI practitioners to help enhance the performance of language understanding and gain expertise with hands-on implementation of transformers using PyTorch, TensorFlow, Hugging Face, Trax, and AllenNLP. | ||
| 505 | 0 | |a Table of Contents Getting Started with the Model Architecture of the Transformer Fine-Tuning BERT Models Pretraining a RoBERTa Model from Scratch Downstream NLP Tasks with Transformers Machine Translation with the Transformer Text Generation with OpenAI GPT-2 and GPT-3 Models Applying Transformers to Legal and Financial Documents for AI Text Summarization Matching Tokenizers and Datasets Semantic Role Labeling with BERT-Based Transformers Let Your Data Do the Talking: Story, Questions, and Answers Detecting Customer Emotions to Make Predictions Analyzing Fake News with Transformers Appendix: Answers to the Questions. | |
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
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| 650 | 0 | |a Artificial intelligence |x Data processing. | |
| 650 | 0 | |a Artificial intelligence |x Software. | |
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Cloud computing. | |
| 650 | 6 | |a Intelligence artificielle |x Informatique. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Infonuagique. | |
| 650 | 7 | |a Artificial intelligence. |2 bicssc | |
| 650 | 7 | |a Natural language & machine translation. |2 bicssc | |
| 650 | 7 | |a Neural networks & fuzzy systems. |2 bicssc | |
| 650 | 7 | |a Computers |x Intelligence (AI) & Semantics. |2 bisacsh | |
| 650 | 7 | |a Computers |x Natural Language Processing. |2 bisacsh | |
| 650 | 7 | |a Computers |x Neural Networks. |2 bisacsh | |
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| 650 | 7 | |a Artificial intelligence |x Data processing |2 fast | |
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| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 655 | 7 | |a Software |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Rothman, Denis |t Transformers for Natural Language Processing |d Birmingham : Packt Publishing, Limited,c2021 |z 9781800565791 |
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