Transformers for Natural Language Processing and Computer Vision: Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3
Sprache: Englisch
Verlag: Packt Publishing Limited, 2024
- Softcover
- Gebraucht
Anbieter: World of Books Inc, Montgomery, IL, USAWorld of Books Inc
AbeBooks-Verkäufer/-in seit 23. März 2026
Zustand: Gebraucht - Gut
EUR 28,27
Anzahl: 2 verfügbar
In den WarenkorbArtikelbeschreibung vom Verkäufer
The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal AI, risk mitigation, and practical implementations with ChatGPT, Hugging Face, and Vertex AI Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Compare and contrast 20+ models (including GPT, BERT, and Llama) and multiple platforms and libraries to find the right solution for your project Apply RAG with LLMs using customized texts and embeddings Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, practical applications, and popular platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through a range of transformer architectures from foundation models and generative AI. You?ll pretrain and fine-tune LLMs and work through different use cases, from summarization to question-answering systems leveraging embedding-based search. You'll also implement Retrieval Augmented Generation (RAG) to enhance accuracy and gain greater control over your LLM outputs. Additionally, you?ll understand common LLM risks, such as hallucinations, memorization, and privacy issues, and implement mitigation strategies using moderation models alongside rule-based systems and knowledge integration. Dive into generative vision transformers and multimodal architectures, and build practical applications, such as image and video classification. Go further and combine different models and platforms to build AI solutions and explore AI agent capabilities. This book provides you with an understanding of transformer architectures, including strategies for pretraining, fine-tuning, and LLM best practices.What you will learn Breakdown and understand the architectures of the Transformer, BERT, GPT, T5, PaLM, ViT, CLIP, and DALL-E Fine-tune BERT, GPT, and PaLM models Learn about different tokenizers and the best practices for preprocessing language data Pretrain a RoBERTa model from scratch Implement retrieval augmented generation and rules bases to mitigate hallucinations Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Go in-depth into vision transformers with CLIP, DALL-E, and GPT Who this book is forThis book is ideal for NLP and CV engineers, data scientists, machine learning practitioners, software developers, and technical leaders looking to advance their expertise in LLMs and generative AI or explore latest industry trends. Familiarity with Python and basic machine learning concepts will help you fully understand the use cases and code examples. However, hands-on examples involving LLM user interfaces, prompt engineering, and no-code model building ensure this book remains accessible to anyone curious about the AI revolution.…
Bestandsnummer des Verkäufers CIN1805128728VG
- Titel
- Transformers for Natural Language Processing and Computer Vision: Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3
- Autor
- Denis Rothman
- Verlag
- Packt Publishing Limited
- Veröffentlichungsjahr
- 2024
- Zustand
- Very Good
- Einband
- Paperback
- Sprache
- Englisch
- ISBN-10
- 1805128728
- ISBN-13
- 9781805128724
- Ausgabe
- 3. Auflage
The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal AI, risk mitigation, and practical implementations with ChatGPT, Hugging Face, and Vertex AI
Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free
Key Features
- Compare and contrast 20+ models (including GPT, BERT, and Llama) and multiple platforms and libraries to find the right solution for your project
- Apply RAG with LLMs using customized texts and embeddings
- Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases
Book Description
Transformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, practical applications, and popular platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV).
The book guides you through a range of transformer architectures from foundation models and generative AI. You’ll pretrain and fine-tune LLMs and work through different use cases, from summarization to question-answering systems leveraging embedding-based search. You'll also implement Retrieval Augmented Generation (RAG) to enhance accuracy and gain greater control over your LLM outputs. Additionally, you’ll understand common LLM risks, such as hallucinations, memorization, and privacy issues, and implement mitigation strategies using moderation models alongside rule-based systems and knowledge integration.
Dive into generative vision transformers and multimodal architectures, and build practical applications, such as image and video classification. Go further and combine different models and platforms to build AI solutions and explore AI agent capabilities.
This book provides you with an understanding of transformer architectures, including strategies for pretraining, fine-tuning, and LLM best practices.
What you will learn
- Breakdown and understand the architectures of the Transformer, BERT, GPT, T5, PaLM, ViT, CLIP, and DALL-E
- Fine-tune BERT, GPT, and PaLM models
- Learn about different tokenizers and the best practices for preprocessing language data
- Pretrain a RoBERTa model from scratch
- Implement retrieval augmented generation and rules bases to mitigate hallucinations
- Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP
- Go in-depth into vision transformers with CLIP, DALL-E, and GPT
Who this book is for
This book is ideal for NLP and CV engineers, data scientists, machine learning practitioners, software developers, and technical leaders looking to advance their expertise in LLMs and generative AI or explore latest industry trends.
Familiarity with Python and basic machine learning concepts will help you fully understand the use cases and code examples. However, hands-on examples involving LLM user interfaces, prompt engineering, and no-code model building ensure this book remains accessible to anyone curious about the AI revolution.
Table of Contents
- What are Transformers?
- Getting Started with the Architecture of the Transformer Model
- Emergent vs Downstream Tasks: The Unseen Depths of Transformers
- Advancements in Translations with Google Trax, Google Translate, and Gemini
- Diving into Fine-Tuning through BERT
- Pretraining a Transformer from Scratch through RoBERTa
- The Generative AI Revolution with ChatGPT
- Fine-Tuning OpenAI GPT Models
- Shattering the Black Box with Interpretable Tools
(N.B. Please use the Read Sample opti
The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal AI, risk mitigation, and practical implementations with ChatGPT, Hugging Face, and Vertex AI
Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free
Key Features
- Compare and contrast 20+ models (including GPT, BERT, and Llama) and multiple platforms and libraries to find the right solution for your project
- Apply RAG with LLMs using customized texts and embeddings
- Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases
Book Description
Transformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, practical applications, and popular platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV).
The book guides you through a range of transformer architectures from foundation models and generative AI. You’ll pretrain and fine-tune LLMs and work through different use cases, from summarization to question-answering systems leveraging embedding-based search. You'll also implement Retrieval Augmented Generation (RAG) to enhance accuracy and gain greater control over your LLM outputs. Additionally, you’ll understand common LLM risks, such as hallucinations, memorization, and privacy issues, and implement mitigation strategies using moderation models alongside rule-based systems and knowledge integration.
Dive into generative vision transformers and multimodal architectures, and build practical applications, such as image and video classification. Go further and combine different models and platforms to build AI solutions and explore AI agent capabilities.
This book provides you with an understanding of transformer architectures, including strategies for pretraining, fine-tuning, and LLM best practices.
What you will learn
- Breakdown and understand the architectures of the Transformer, BERT, GPT, T5, PaLM, ViT, CLIP, and DALL-E
- Fine-tune BERT, GPT, and PaLM models
- Learn about different tokenizers and the best practices for preprocessing language data
- Pretrain a RoBERTa model from scratch
- Implement retrieval augmented generation and rules bases to mitigate hallucinations
- Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP
- Go in-depth into vision transformers with CLIP, DALL-E, and GPT
Who this book is for
This book is ideal for NLP and CV engineers, data scientists, machine learning practitioners, software developers, and technical leaders looking to advance their expertise in LLMs and generative AI or explore latest industry trends.
Familiarity with Python and basic machine learning concepts will help you fully understand the use cases and code examples. However, hands-on examples involving LLM user interfaces, prompt engineering, and no-code model building ensure this book remains accessible to anyone curious about the AI revolution.
Table of Contents
- What are Transformers?
- Getting Started with the Architecture of the Transformer Model
- Emergent vs Downstream Tasks: The Unseen Depths of Transformers
- Advancements in Translations with Google Trax, Google Translate, and Gemini
- Diving into Fine-Tuning through BERT
- Pretraining a Transformer from Scratch through RoBERTa
- The Generative AI Revolution with ChatGPT
- Fine-Tuning OpenAI GPT Models
- Shattering the Black Box with Interpretable Tools
(N.B. Please use the Read Sample option to see further chapters)
on to see further chapters)„Inhaltsangabe“ gehört möglicherweise zu einer anderen Auflage dieses Titels.
Über die Autorin bzw. den Autor
Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive Natural Language Processing (NLP) chatbots applied as an automated language teacher for Moet et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.
„Über diesen Titel“ gehört möglicherweise zu einer anderen Auflage dieses Titels.
World of Books Inc
Montgomery, IL, USA
AbeBooks-Verkäufer/-in seit 23. März 2026
Versandkosten innerhalb von USA
| Artikel | 4 bis 12 Werktage | 3 bis 6 Werktage |
|---|---|---|
| Erster Artikel | EUR 0,00 | EUR 9,63 |
Zahlungsarten
Shop-Beschreibung
Founded in 2002, World of Books is a leading online destination for buying and selling both preloved and new books, committed to making sustainable reading accessible to all. With a mission to help people read more and waste less, World of Books offers a huge range of affordable, high-quality books — giving both new and preloved titles a second life. The company also operates World of Books – Sell Your Books, an easy-to-use platform that allows customers to trade in unwanted books for cash, helping to keep books in circulation while promoting sustainability. As a Certified B Corp, World of Books is driven by a vision to become the world’s largest and most sustainable dedicated online bookstore. The company measures its success through the positive environmental impact it creates, the value it provides to customers, and its ability to operate profitably while supporting its sustainable mission …
Spezialisierung
Second Hand - All GenreUnternehmensdaten der Verkäuferin bzw. des Verkäufers
SBYB, Inc.
900 Knell Road
Montgomery, IL USA 60538
Widerrufsrecht
Wenn Sie Verbraucher sind, können Sie gemäß den folgenden Bestimmungen vom Vertrag zurücktreten. Verbraucher ist jede natürliche Person, die zu Zwecken handelt, die nicht ihrer kaufmännischen, gewerblichen, künstlerischen oder beruflichen Tätigkeit zugerechnet werden können.
Informationen zum Widerrufsrecht
Gesetzliches Widerrufsrecht
Sie haben das Recht, den Vertrag innerhalb von 14 Tagen ohne Angabe von Gründen zu widerrufen.
Die Widerrufsfrist beträgt 14 Tage ab dem Tag, an dem Sie oder ein von Ihnen benannter Dritter, der nicht der Transporteur ist, die letzte Ware oder den letzten Posten oder das letzte Exemplar in Besitz genommen hat.
Um das Widerrufsrecht auszuüben, füllen Sie auf unserer Website unter „Meine Einkäufe" in „Mein Nutzerkonto" eine eindeutige Erklärung elektronisch aus und senden Sie sie ab. Wir werden Ihnen unverzüglich eine Bestätigung über den Eingang eines solchen Widerrufs auf einem dauerhaften Datenträger (z. B. per E-Mail) übermitteln.
Um die Widerrufsfrist einzuhalten, reicht es aus, dass Sie Ihre Mitteilung über die Ausübung des Widerrufsrechts vor Ablauf der Widerrufsfrist absenden.
Auswirkungen des Widerrufs
Wenn Sie diesen Vertrag widerrufen, erstatten wir Ihnen alle Zahlungen, die wir von Ihnen erhalten haben, einschließlich der Lieferkosten (mit Ausnahme der zusätzlichen Kosten, die entstehen, wenn Sie eine andere Art der Lieferung als die von uns angebotene günstigste Standardlieferung gewählt haben).
Wir können einen Abzug von der Rückerstattung für den Wertverlust der gelieferten Waren vornehmen, wenn der Verlust auf eine unnötige Behandlung durch Sie zurückzuführen ist.
Wir werden die Rückerstattung unverzüglich und nicht später als 14 Tage nach dem Tag vornehmen, an dem wir über Ihre Entscheidung, diesen Vertrag zu widerrufen, informiert wurden.
Für die Rückerstattung verwenden wir dasselbe Zahlungsmittel, das Sie für die ursprüngliche Transaktion verwendet haben, es sei denn, Sie haben ausdrücklich etwas anderes vereinbart; in keinem Fall werden Ihnen aufgrund einer solchen Rückerstattung Gebühren berechnet.
Wir können die Rückzahlung verweigern, bis wir die Waren wieder zurückerhalten haben oder Sie den Nachweis erbracht haben, dass Sie die Waren zurückgesandt haben, je nachdem, was eher eintritt.
Sie müssen die Waren unverzüglich und in jedem Fall spätestens 14 Tage ab dem Tag, an dem Sie uns über den Widerruf dieses Vertrags unterrichten, an World of Books Inc, Montgomery, Illinois, U.S.A., zurücksenden oder übergeben. Die Frist ist eingehalten, wenn Sie die Ware vor Ablauf der Frist von 14 Tagen zurücksenden. Sie müssen die direkten Kosten der Rücksendung der Waren tragen. Sie haften nur für einen etwaigen Wertverlust der Waren, der auf eine Behandlung zurückzuführen ist, die nicht zur Prüfung der Art, Eigenschaften und Funktionsweise der Waren erforderlich ist.
Ausnahmen vom Widerrufsrecht
Das Widerrufsrecht gilt nicht für:
- Die Lieferung von Zeitungen, Zeitschriften oder Magazinen mit Ausnahme von Abonnementverträgen; und
- Die Lieferung digitaler Inhalte, die nicht auf einem physischen Medium (z. B. auf einer CD oder DVD) geliefert werden, wenn Sie bei Ihrer Bestellung akzeptiert haben, dass wir mit der Lieferung beginnen können und dass Sie nach Beginn der Lieferung den Vertrag nicht mehr widerrufen können.