Seller: Arcadia Books, Inc., Hoschton, GA, U.S.A.
Soft cover. Condition: Good. 2nd Edition. There is some very light stain on the bottom edge of the pages; some pages have a very light waviness in the same area. The spine tilts \/ curves slightly. The top edge of the pages has a shallow scratch (see pictures). The covers have some light wear and minor creasing. The pages are free from markings and highlighting. Quite useable if you don't mind the light staining on the edge. See pictures for more details.
Published by Packt Publishing
Seller: Academic Book Solutions, Medford, NY, U.S.A.
paperback. Condition: VeryGood. Warped, A copy that may have been read, very minimal wear and tear. May have a remainder mark.
Seller: WeBuyBooks, Rossendale, LANCS, United Kingdom
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Add to basketCondition: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.
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Seller: Mispah books, Redhill, SURRE, United Kingdom
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: Toscana Books, AUSTIN, TX, U.S.A.
Paperback. Condition: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 2nd ed. edition NO-PA16APR2015-KAP.
Seller: Toscana Books, AUSTIN, TX, U.S.A.
Paperback. Condition: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Published by Packt Publishing, Limited, 2021
ISBN 10: 1800565798 ISBN 13: 9781800565791
Language: English
Seller: Majestic Books, Hounslow, United Kingdom
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Published by Packt Publishing Limited, 2021
ISBN 10: 1800565798 ISBN 13: 9781800565791
Language: English
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by Packt Publishing Limited, 2022
ISBN 10: 1803247339 ISBN 13: 9781803247335
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
US$ 118.48
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Published by Packt Publishing Limited, 2021
ISBN 10: 1800565798 ISBN 13: 9781800565791
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
US$ 130.32
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Seller: Biblios, Frankfurt am main, HESSE, Germany
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Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - OpenAI's GPT-3, ChatGPT, GPT-4 and Hugging Face transformers for language tasks in one book. Get a taste of the future of transformers, including computer vision tasks and code writing and assistance.Purchase of the print or Kindle book includes a free Elektronisches Buch in PDF formatKey Features:Pretrain a BERT-based model from scratch using Hugging FaceFine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your dataPerform root cause analysis on hard NLP problemsBook Description:Transformers are.well.transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses.You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model.If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides.The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details).You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using Codex.By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective!What You Will Learn:Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-EDiscover new techniques to investigate complex language problemsCompare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformersCarry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3Measure the productivity of key transformers to define their scope, potential, and limits in productionWho this book is for:If you want to learn about and apply transformers to your natural language (and image) data, this book is for you.You'll need a good understanding of Python and deep learning and a basic understanding of NLP to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters. And, don't worry if you get stuck or have questions; this book gives you direct access to our AI/ML community and author, Denis Rothman. So, he'll be there to guide you on your transformers journey!
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Take your NLP knowledge to the next level and become an AI language understanding expert by mastering the quantum leap of Transformer neural network modelsKey FeaturesBuild and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning modelsGo through hands-on applications in Python using Google Colaboratory Not Elektronisches Buch with nothing to install on a local machineTest transformer models on advanced use casesBook DescriptionThe 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 with transformers.The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face.The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification.By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets.What You Will LearnUse the latest pretrained transformer modelsGrasp the workings of the original Transformer, GPT-2, BERT, T5, and other transformer modelsCreate language understanding Python programs using concepts that outperform classical deep learning modelsUse a variety of NLP platforms, including Hugging Face, Trax, and AllenNLPApply Python, TensorFlow, and Keras programs to sentiment analysis, text summarization, speech recognition, machine translations, and moreMeasure the productivity of key transformers to define their scope, potential, and limits in productionWho this book is forSince the book does not teach basic programming, you must be familiar with neural networks, Python, PyTorch, and TensorFlow in order to learn their implementation with Transformers.Readers who can benefit the most from this book include experienced deep learning & NLP practitioners and data analysts & data scientists who want to process the increasing amounts of language-driven data.