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210823 ||| eng |
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|a 1800568630
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| 050 |
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4 |
|a Q336
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| 100 |
1 |
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|a Rothman, Denis
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| 245 |
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|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
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| 260 |
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|a Birmingham
|b Packt Publishing, Limited
|c 2021
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| 300 |
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|a 385 p.
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| 505 |
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|a Includes bibliographical references and index
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| 505 |
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|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
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| 653 |
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|a Computers / Neural Networks / bisacsh
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| 653 |
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|a Artificial intelligence / bicssc
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| 653 |
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|a Artificial intelligence / Data processing / http://id.loc.gov/authorities/subjects/sh85008182
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| 653 |
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|a Neural networks & fuzzy systems / bicssc
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| 653 |
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|a Cloud computing / fast
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| 653 |
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|a Python (Computer program language) / fast
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| 653 |
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|a Infonuagique
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| 653 |
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|a Python (Computer program language) / http://id.loc.gov/authorities/subjects/sh96008834
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| 653 |
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|a Artificial intelligence / fast
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| 653 |
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|a Computers / Natural Language Processing / bisacsh
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| 653 |
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|a Cloud computing / http://id.loc.gov/authorities/subjects/sh2008004883
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| 653 |
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|a Artificial intelligence / Data processing / fast
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| 653 |
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|a Intelligence artificielle / Informatique
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| 653 |
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|a Artificial intelligence / Software
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| 653 |
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|a Computers / Intelligence (AI) & Semantics / bisacsh
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| 653 |
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|a Natural language & machine translation / bicssc
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| 653 |
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|a Python (Langage de programmation)
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
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|a Description based upon print version of record
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| 015 |
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|a GBC3F7658
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| 776 |
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|z 9781800568631
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| 776 |
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|z 1800565798
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| 776 |
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|z 9781800565791
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| 856 |
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|u https://learning.oreilly.com/library/view/~/9781800565791/?ar
|x Verlag
|3 Volltext
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| 082 |
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|a 331
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| 082 |
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|a 006.3
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| 520 |
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|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.
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