Introduction to Transformers for NLP (eBook)
XI, 165 Seiten
Apress (Verlag)
978-1-4842-8844-3 (ISBN)
Get a hands-on introduction to Transformer architecture using the Hugging Face library. This book explains how Transformers are changing the AI domain, particularly in the area of natural language processing.
This book covers Transformer architecture and its relevance in natural language processing (NLP). It starts with an introduction to NLP and a progression of language models from n-grams to a Transformer-based architecture. Next, it offers some basic Transformers examples using the Google colab engine. Then, it introduces the Hugging Face ecosystem and the different libraries and models provided by it. Moving forward, it explains language models such as Google BERT with some examples before providing a deep dive into Hugging Face API using different language models to address tasks such as sentence classification, sentiment analysis, summarization, and text generation.
After completing Introduction to Transformers for NLP, you will understand Transformer concepts and be able to solve problems using the Hugging Face library.
- Understand language models and their importance in NLP and NLU (Natural Language Understanding)
- Master Transformer architecture through practical examples
- Use the Hugging Face library in Transformer-based language models
- Create a simple code generator in Python based on Transformer architecture
Shashank Mohan Jain has been working in the IT industry for around 20 years mainly in the areas of cloud computing, machine learning and distributed systems. He has keen interests in virtualization techniques, security, and complex systems. Shashank has software patents to his name in the area of cloud computing, IoT, and machine learning. He is a speaker at multiple reputed cloud conferences. Shashank holds Sun, Microsoft, and Linux kernel certifications.
Get a hands-on introduction to Transformer architecture using the Hugging Face library. This book explains how Transformers are changing the AI domain, particularly in the area of natural language processing.This book covers Transformer architecture and its relevance in natural language processing (NLP). It starts with an introduction to NLP and a progression of language models from n-grams to a Transformer-based architecture. Next, it offers some basic Transformers examples using the Google colab engine. Then, it introduces the Hugging Face ecosystem and the different libraries and models provided by it. Moving forward, it explains language models such as Google BERT with some examples before providing a deep dive into Hugging Face API using different language models to address tasks such as sentence classification, sentiment analysis, summarization, and text generation.After completing Introduction to Transformers for NLP, you will understand Transformer concepts and be able to solve problems using the Hugging Face library.What You Will LearnUnderstand language models and their importance in NLP and NLU (Natural Language Understanding)Master Transformer architecture through practical examplesUse the Hugging Face library in Transformer-based language modelsCreate a simple code generator in Python based on Transformer architectureWho This Book Is ForData Scientists and software developers interested in developing their skills in NLP and NLU (Natural Language Understanding)
| Erscheint lt. Verlag | 20.10.2022 |
|---|---|
| Zusatzinfo | XI, 165 p. 80 illus. |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Artificial Intelligence • Deep learning • Hugging Face • machine learning • Natural Language Processing • Natural language understanding • Python • Transformers |
| ISBN-10 | 1-4842-8844-0 / 1484288440 |
| ISBN-13 | 978-1-4842-8844-3 / 9781484288443 |
| Haben Sie eine Frage zum Produkt? |
PDF (Wasserzeichen)Größe: 6,0 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich
