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Beschreibung
This book, "Hands-On Implementation of Transformer Models with Hugging Face," serves as a comprehensive guide for understanding and applying transformer models in Natural Language Processing (NLP). It covers fundamental concepts, step-by-step instructions for fine-tuning and deploying models, practical applications, and ethical considerations. Through detailed explanations and code examples, readers will learn how to leverage Hugging Face's powerful library to build state-of-the-art NLP solutions, ensuring responsible and effective use of AI technologies.
This book, "Hands-On Implementation of Transformer Models with Hugging Face," serves as a comprehensive guide for understanding and applying transformer models in Natural Language Processing (NLP). It covers fundamental concepts, step-by-step instructions for fine-tuning and deploying models, practical applications, and ethical considerations. Through detailed explanations and code examples, readers will learn how to leverage Hugging Face's powerful library to build state-of-the-art NLP solutions, ensuring responsible and effective use of AI technologies.
Über den Autor
Dr. Rupesh Kumar, a professor at K R Mangalam University, specializes in optimization and AI. With 10+ years of experience, he has published extensively and led research projects in engineering design and smart grid management. An accomplished educator, he has authored several books and actively contributes to professional organizations.
Details
Erscheinungsjahr: 2024
Fachbereich: Allgemeines
Genre: Importe, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: 80 S.
ISBN-13: 9786207808137
ISBN-10: 6207808134
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Kumar Tipu, Rupesh
Hersteller: LAP LAMBERT Academic Publishing
Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, ?-1039 Riga, customerservice@vdm-vsg.de
Maße: 220 x 150 x 5 mm
Von/Mit: Rupesh Kumar Tipu
Erscheinungsdatum: 24.06.2024
Gewicht: 0,137 kg
Artikel-ID: 129655770

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